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18th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2023) [[electronic resource] ] : Salamanca, Spain, September 5–7, 2023, Proceedings, Volume 1 / / edited by Pablo García Bringas, Hilde Pérez García, Francisco Javier Martínez de Pisón, Francisco Martínez Álvarez, Alicia Troncoso Lora, Álvaro Herrero, José Luis Calvo Rolle, Héctor Quintián, Emilio Corchado
18th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2023) [[electronic resource] ] : Salamanca, Spain, September 5–7, 2023, Proceedings, Volume 1 / / edited by Pablo García Bringas, Hilde Pérez García, Francisco Javier Martínez de Pisón, Francisco Martínez Álvarez, Alicia Troncoso Lora, Álvaro Herrero, José Luis Calvo Rolle, Héctor Quintián, Emilio Corchado
Autore García Bringas Pablo
Edizione [1st ed. 2023.]
Pubbl/distr/stampa Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Descrizione fisica 1 online resource (305 pages)
Disciplina 006.3
Altri autori (Persone) Pérez GarcíaHilde
Martínez de PisónFrancisco Javier
Martínez ÁlvarezFrancisco
Troncoso LoraAlicia
HerreroÁlvaro
Calvo RolleJosé Luis
QuintiánHéctor
CorchadoEmilio
Collana Lecture Notes in Networks and Systems
Soggetto topico Computational intelligence
Industrial engineering
Production engineering
Computational Intelligence
Industrial and Production Engineering
ISBN 3-031-42529-4
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Contents -- Deep Learning, Fuzzy Logic and Evolutionary Computation -- Text Classification for Automatic Distribution of Review Notes in Movie Production -- 1 Introduction -- 2 Dataset -- 3 Methodology -- 3.1 Data Cleaning -- 3.2 Label Estimation -- 3.3 Tokenization -- 3.4 Classification -- 4 Experiments and Results -- 5 Conclusions and Future Work -- References -- Extended Rank-Based Ant Colony Optimization Algorithm for Traveling Salesman Problem -- 1 Introduction -- 2 Ant Colony Optimization -- 3 Proposed ACO Algorithm Plus Local Search -- 4 Results -- 5 Conclusions and Future Work -- References -- Multi-scale Neural Model for Tool-Narayanaswamy-Moynihan Model Parameter Extraction -- 1 Introduction -- 2 Materials and Methods -- 2.1 TNM Model and Its Parameters -- 2.2 Multi-scale Convolutional Neural Model -- 2.3 Dataset -- 3 Experiments and Results -- 3.1 Training Details -- 3.2 Evaluation of Multi-scale Neural Model -- 4 Conclusion -- References -- Application of Fuzzy Logic to the Risk Assessment of Production Machines Failures -- 1 Introduction -- 2 Linguistic Values and Its Analysis in Risk Assessment -- 3 Fuzzy FMEA in the Risk Assessment of Production Downtime -- 4 Conclusion -- References -- First Approach of an Intelligent Automatic System for Aircraft Flap/Slat Positioning -- 1 Introduction -- 2 Brief State of the Art -- 3 Description of the Problem Addressed -- 4 Automation of the Flap/Slat Positioning System -- 4.1 General System Architecture -- 4.2 Fuzzy Decision Block -- 5 Simulation Results and Discussion -- 6 Conclusions and Future Works -- References -- Fuzzy Aggregators in Practice: Meta-Model and Implementation -- 1 Introduction -- 2 Background -- 3 Meta-Modeling Fuzzy Aggregators -- 4 Novel Constructs in J-CO-QL+ and Case Study -- 4.1 Case Study.
4.2 Declaring Fuzzy Operator and Fuzzy Aggregators -- 4.3 Soft Querying -- 5 Conclusions -- References -- Machine Learning and Data Mining -- Model-Based Design of the IMO-NMPC Strategy: Real-Time Implementation -- 1 Introduction -- 2 Workflow: From Simulation to Real-Time Execution -- 2.1 Phases -- 3 iMO-NMPC Strategy Implementation -- 4 Experiments -- 4.1 PHASE 3: Simulink Desktop Real-Time Experiments -- 4.2 PHASE 4: Simulink Real-Time Experiments -- 5 Results -- 5.1 SNL1/SNL5 SISO System Simulink Desktop Real-Time -- 5.2 SNL1/SNL5 SISO System Simulink Real-Time (Speedgoat) -- 5.3 SNL1-SNL1 MIMO System Simulink Real-Time (Speedgoat) -- 5.4 SNL1-SNL5 MIMO System Simulink Real-Time (Speedgoat) -- 6 Conclusions -- References -- Hyperspectral Technology for Oil Spills Detection by Using Artificial Neural Network Classifier -- 1 Introduction -- 2 Materials and Methods -- 2.1 Principal Component Analysis (PCA) -- 2.2 Artificial Neural Networks (ANNs) and Bayesian Optimization -- 3 Results and Discussion -- 4 Conclusions -- References -- Neuron Characterization in Complex Cultures Using a Combined YOLO and U-Net Segmentation Approach -- 1 Introduction -- 2 State of the Art -- 3 Materials and Methods -- 3.1 Experimental Setup -- 3.2 Experimental Procedure -- 4 Results and Discussion -- References -- Effectiveness of Quantum Computing in Image Processing for Burr Detection -- 1 Introduction -- 2 Quantum Computing -- 3 Burr Detection -- 4 Proposed Architecture -- 5 Experimental Results -- 6 Conclusions -- References -- Categorization of CoAP DoS Attack Based on One-Class Boundary Methods -- 1 Introduction -- 2 Case Study -- 3 Methods -- 3.1 Approximate Convex Hull -- 3.2 K Nearest Neighborhood -- 3.3 One-Class Support Vector Machine -- 4 Experiments -- 5 Results -- 6 Conclusions and Future Works -- References.
TinyNARM: Simplifying Numerical Association Rule Mining for Running on Microcontrollers -- 1 Introduction -- 2 Basic Information -- 2.1 Numerical Association Rule Mining -- 2.2 Classical NARM Using Evolutionary Approaches -- 2.3 TinyML -- 3 TinyNARM -- 4 Experiments and Results -- 4.1 Datasets -- 4.2 Experimental Environment -- 4.3 Results -- 4.4 Discussion -- 5 Conclusion -- References -- Fault Detection in Biological Methanation Process Using Machine Learning: A Comparative Study of Different Algorithms -- 1 Introduction -- 2 Biological Methanation Model and Optimization -- 2.1 Extended Anaerobic Digestion Model (ADM1 ME) -- 2.2 Optimal Operation -- 2.3 ADM1 ME Disturbances and Dataset Generation -- 3 Results and Discussion -- 4 Conclusions and Future Work -- References -- Soft Computing Applications -- Comparative Study of Regression Models Applied to the Prediction of Energy Generated by a Micro Wind Turbine -- 1 Introduction -- 2 Case Study -- 2.1 Sotavento Experimental Bioclimatic House -- 2.2 Dataset -- 3 Applied Methods -- 4 Experiment Setup and Results -- 4.1 Experiments Setup -- 4.2 Metrics -- 4.3 Results -- 5 Conclusions and Future Work -- References -- Comparative Study of Wastewater Treatment Plant Feature Selection for COD Prediction -- 1 Introduction -- 2 Wastewater Treatment Plant Under Study -- 3 Applied Methods -- 3.1 Feature Selection -- 3.2 Regression Techniques -- 4 Experiments and Results -- 4.1 Experiment's Setup -- 4.2 Results -- 4.3 Analysis of Results -- 5 Conclusions and Future Work -- References -- Machine Learning Based System for Detecting Battery State-of-Health -- 1 Introduction -- 2 Case Study -- 3 Materials and Methods -- 3.1 Random Forest -- 3.2 Multilayer Perceptron -- 3.3 K-Nearest Neighbors -- 3.4 Gaussian Process Classifier -- 3.5 Support Vector Classifier -- 4 Experimental Setup -- 5 Results and Analysis.
6 Conclusions and Future Work -- References -- Leveraging Smart Meter Data for Adaptive Consumer Profiling -- 1 Introduction -- 2 Related Work -- 3 Workflow for Adaptive Clustering Pipeline -- 3.1 General Approach -- 3.2 Dataset for Analysis -- 3.3 Description of the Data Pipeline -- 4 Data Analysis -- 4.1 Ground Truth Cluster Selection and Analysis -- 4.2 Cold-Start Analysis -- 5 Conclusions -- References -- Managing Pandemics Through Agent-Based Simulation: A Case Study Based on COVID-19 -- 1 Managing Pandemics: A Challenging Decision-Making Process -- 2 Review of Simulation Tools to Model Pandemics Evolution -- 3 Modelling Pandemics Evolution Through an Agent-Based Model -- 3.1 Disease Spread Modelling -- 3.2 Disease Evolution and Impact on Healthcare System -- 3.3 Modelling Pharmacological and Non-Pharmacological Measures -- 4 Prototype Implementation Based on COVID-19 -- 5 Validation -- 5.1 Baseline Scenario -- 5.2 Comparison of Non-pharmacological Measures and Baseline Scenario -- 6 Conclusions -- References -- Missing Values Imputation for Visualizing the Air Quality Evolution During the COVID-19 Pandemic in Madrid -- 1 Introduction -- 2 Techniques Applied -- 2.1 Imputation and Regression -- 2.2 Visualization -- 3 A Real-Life Case Study -- 4 Experiments and Results -- 5 Conclusions and Future Work -- References -- Special Session 1: Time Series Forecasting in Industrial and Environmental Applications -- Feature Selection Guided by CVOA Metaheuristic for Deep Neural Networks: Application to Multivariate Time Series Forecasting -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Dataset -- 3.2 Models -- 3.3 Evaluation Metric -- 3.4 Optimization Process -- 4 Results and Discussion -- 4.1 Performance Results -- 4.2 Number of Features Analysis -- 4.3 Best and Worst Predictions Analysis -- 5 Conclusions and Future Work -- References.
Neuroevolutionary Transfer Learning for Time Series Forecasting -- 1 Introduction -- 2 Our Proposal -- 3 Results -- 4 Conclusions -- References -- Machine Learning Approaches for Predicting Tree Growth Trends Based on Basal Area Increment -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Data Acquisition -- 3.2 Data Cleaning -- 3.3 Data Transformation -- 3.4 Machine Learning Algorithms -- 3.5 Model Evaluation -- 4 Results -- 4.1 Input Data -- 4.2 Tree Growth Prediction -- 5 Conclusions and Future Work -- References -- Forecasting Greenhouse Temperature Using Machine Learning Models: Optimizing Crop Production in Andalucia -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Experimental Setup -- 3.2 Machine Learning Models -- 4 Results and Discussion -- 4.1 Data Description -- 4.2 Experimental Results -- 5 Conclusions -- References -- Deep Learning and Metaheuristic for Multivariate Time-Series Forecasting -- 1 Introduction -- 2 Methodology -- 2.1 The Proposed Model -- 2.2 Model Training -- 2.3 Model Evaluation -- 3 Results -- 4 Conclusions -- References -- An Approach to Enhance Time Series Forecasting by Fast Fourier Transform -- 1 Introduction -- 2 Background -- 3 Methodology -- 3.1 Dataset -- 3.2 Feature Engineering -- 3.3 Models to Use -- 4 Results and Discussion -- 5 Conclusions -- References -- Comparative Study of Open Source Database Management Systems to Enable Predictive Maintenance of Autonomous Guided Vehicles -- 1 Introduction -- 2 Use Case -- 3 Methodology -- 3.1 Database Management Systems Under Study -- 3.2 Comparison Procedure -- 3.3 Comparison Perspectives -- 4 Experiments and Results -- 4.1 Functional Comparison -- 4.2 Performance Evaluation -- 5 Conclusions and Future Work -- References -- Integrated Forecast and Optimization for Retailer Allocation in a Two-Echelon Inventory System -- 1 Introduction.
2 Related Literature.
Record Nr. UNINA-9910743701003321
García Bringas Pablo  
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
18th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2023) [[electronic resource] ] : Salamanca, Spain, September 5–7, 2023, Proceedings, Volume 2 / / edited by Pablo García Bringas, Hilde Pérez García, Francisco Javier Martínez de Pisón, Francisco Martínez Álvarez, Alicia Troncoso Lora, Álvaro Herrero, José Luis Calvo Rolle, Héctor Quintián, Emilio Corchado
18th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2023) [[electronic resource] ] : Salamanca, Spain, September 5–7, 2023, Proceedings, Volume 2 / / edited by Pablo García Bringas, Hilde Pérez García, Francisco Javier Martínez de Pisón, Francisco Martínez Álvarez, Alicia Troncoso Lora, Álvaro Herrero, José Luis Calvo Rolle, Héctor Quintián, Emilio Corchado
Autore García Bringas Pablo
Edizione [1st ed. 2023.]
Pubbl/distr/stampa Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Descrizione fisica 1 online resource (376 pages)
Disciplina 006.3
Altri autori (Persone) Pérez GarcíaHilde
Martínez de PisónFrancisco Javier
Martínez ÁlvarezFrancisco
Troncoso LoraAlicia
HerreroÁlvaro
Calvo RolleJosé Luis
QuintiánHéctor
CorchadoEmilio
Collana Lecture Notes in Networks and Systems
Soggetto topico Computational intelligence
Industrial engineering
Production engineering
Computational Intelligence
Industrial and Production Engineering
ISBN 3-031-42536-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Contents -- Special Session 2: Technological Foundations and Advanced Applications of Drone Systems -- Level 3 Data Fusion -- 1 Ontological Foundations -- 2 Level 3 Data Fusion -- 3 DNN Implementation -- 3.1 CoA Recognition -- 3.2 Event Prediction -- 3.3 Forensic Assessment -- 4 Modeling Courses of Action -- 4.1 Probability of Action -- 4.2 CoA Utility Modeling -- 4.3 Evaluating Response Effectiveness -- References -- Image Classification Using Contrastive Language-Image Pre-training: Application to Aerial Views of Power Line Infrastructures -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Data Selection and Processing -- 3.2 Data Labeling and Caption Generation -- 3.3 CLIP Classifier Selection Methodology -- 4 Results and Discussion -- 4.1 Zero-Shot vs. Few-Shot Classifier -- 4.2 CLIP Fine-Tuning -- 4.3 Final model -- 5 Conclusions -- References -- A Realistic UAS Traffic Generation Tool to Evaluate and Optimize U-Space Airspace Capacity -- 1 Introduction -- 2 Realistic UAS Traffic Generation and Specification -- 2.1 Identification of Common UAS Patterns -- 2.2 Traffic Generation Module -- 2.3 Traffic Specification Module -- 3 Validation of the Traffic Generation and Specification Modules -- 4 Next Steps: Towards a Separation Optimization and Evaluation Framework -- 5 Conclusions -- References -- UAV Airframe Classification Using Acceleration Spectrograms -- 1 Introduction -- 2 State of the Art -- 3 Proposed System -- 3.1 UAV Dataset and Spectrogram Generation -- 3.2 Classification Algorithm -- 4 Experiments and Results -- 5 Conclusions -- References -- Tuning Process Noise in INS/GNSS Fusion for Drone Navigation Based on Evolutionary Algorithms -- 1 Introduction -- 2 INS/GNSS -- 3 Tuning Process -- 4 Case Study -- 4.1 Mission Problem and Simulation Configuration -- 4.2 Filter Parameters.
4.3 Optimization Algorithms -- 5 Results -- 5.1 Results Comparison -- 6 Conclusions -- References -- Special Session 3: Soft Computing Methods in Manufacturing and Management Systems -- Digital Twins of Production Systems Based on Discrete Simulation and Machine Learning Algorithms -- 1 Introduction -- 2 Reinforcement Learning -- 3 A Digital Twin Based on Discrete-Event Simulation as a Reinforcement Learning Agent Environment -- 4 Summary -- References -- Edge Architecture for the Integration of Soft Models Based Industrial AI Control into Industry 4.0 Cyber-Physical Systems -- 1 Introduction -- 2 Related Work -- 3 Architecture -- 4 Validation -- 5 Conclusions -- References -- The Use of Line Simplification and Vibration Suppression Algorithms to Improve the Quality of Determining the Indoor Location in RTLSs -- 1 Introduction -- 1.1 Methods and Technologies for Determining Indoor Location -- 2 Decawave as an Example of RTLS Based on UWB Technology -- 3 Algorithms for Improving RTLS Data -- 3.1 Polyline Simplification Algorithms -- 3.2 Location Instability Suppression Algorithm (LISA) -- 4 Research on the Effectiveness of Algorithms -- 4.1 Discussion of Results -- 5 Summary -- References -- Possibilities of Decision Support in Organizing Production Processes -- 1 Introduction -- 2 Industry 4.0 -- 2.1 Technologies of the Industry 4.0 -- 3 Methodology -- 4 Conclusion -- References -- Special Session 4: Efficiency and Explainability in Machine Learning and Soft Computing -- Efficient Short-Term Time Series Forecasting with Regression Trees -- 1 Introduction -- 2 Materials and Method -- 2.1 Dataset -- 2.2 Experimental Setup -- 2.3 Evaluation Procedure -- 3 Results -- 4 Conclusions -- References -- Generating Synthetic Fetal Cardiotocography Data with Conditional Generative Adversarial Networks -- 1 Introduction -- 2 Methodology.
2.1 Conditional Generative Adversarial Networks -- 2.2 Classifiers -- 3 Experiments -- 3.1 Dataset -- 3.2 CGAN Parameter Tuning -- 3.3 Classifiers Hyperparameter and Parameter Tuning -- 4 Results and Discussion -- 5 Conclusions -- References -- Olive Oil Fly Population Pest Forecasting Using Explainable Deep Learning -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 ADL -- 3.2 Benchmark Algorithms -- 3.3 Explainability -- 4 Experimentation and Results -- 4.1 Input Data -- 4.2 Results and Discussion -- 4.3 Explainability -- 5 Conclusions and Future Work -- References -- Explaining Learned Patterns in Deep Learning by Association Rules Mining -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Preprocessing -- 3.2 Rules Mining -- 3.3 Calculate Metrics -- 3.4 Classify -- 4 Results and Discussion -- 4.1 Experimental Setting -- 4.2 Metrics -- 4.3 Results -- 5 Conclusions -- References -- Special Session 5: Machine Learning and Computer Vision in Industry 4.0 -- A Deep Learning Ensemble for Ultrasonic Weld Quality Control -- 1 Introduction -- 2 Technology -- 2.1 Manufacturing Process -- 2.2 Deep Learning Models -- 3 Deep Learning Ensemble -- 4 Experimental Results -- 5 Conclusion -- References -- Indoor Scenes Video Captioning -- 1 Introduction -- 2 Related Works -- 2.1 Video Captioning -- 2.2 Indoor Scene Captioning -- 3 Methodology -- 4 Experiments -- 4.1 Charades Dataset -- 4.2 Postprocessing -- 4.3 Setup -- 4.4 Results -- 5 Conclusion -- References -- A Multimodal Dataset to Create Manufacturing Digital Twins -- 1 Introduction -- 2 Related Work -- 2.1 Pose Estimation for Action Recognition -- 3 Experimental Setup and Data Acquisition -- 4 Dataset Discussion -- 4.1 Dataset Top View -- 4.2 Dataset Side View -- 4.3 Dataset Front View -- 5 Datarecords -- 6 Conclusions and Future Work -- References.
A Modified Loss Function Approach for Instance Segmentation Improvement and Application in Fish Markets -- 1 Introduction -- 2 Dataset -- 3 Proposed Method -- 4 Experiments and Results -- 4.1 Experimental Setup -- 4.2 Results -- 5 Conclusions -- References -- Parallel Processing Applied to Object Detection with a Jetson TX2 Embedded System -- 1 Introduction -- 2 Methodology -- 3 System Architecture -- 3.1 Software Architecture -- 3.2 Hardware Architecture -- 4 Experimental Results -- 5 Conclusion -- References -- Deep Learning-Based Emotion Detection in Aphasia Patients -- 1 Introduction -- 2 Related Work -- 3 Dataset -- 4 Approach -- 5 Evaluation -- 6 Conclusion -- References -- Defect Detection in Batavia Woven Fabrics by Means of Convolutional Neural Networks -- 1 Introduction and Previous Work -- 2 Related Work -- 3 Case Study -- 4 Methods and Experimentation -- 4.1 Methods -- 4.2 Experimentation -- 5 Results -- 6 Conclusions -- References -- An Image Mosaicing-Based Method for Bird Identification on Edge Computing Devices -- 1 Introduction -- 2 Image Mosaicing-Based Method -- 3 Experiments and Results -- 3.1 Results -- 3.2 Analysis of the Results -- 4 Conclusion -- References -- HoloDemtect: A Mixed Reality Framework for Cognitive Stimulation Through Interaction with Objects -- 1 Introduction -- 2 Related Works -- 3 HoloLens 2 Application -- 3.1 HoloLens 2 API -- 3.2 Implementation Details -- 3.3 Data Collection -- 4 Evaluation of the Proposal -- 4.1 Qualitative Analysis -- 4.2 Quantitative Analysis -- 5 Conclusions -- References -- Accurate Estimation of Parametric Models of the Human Body from 3D Point Clouds -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Obtaining and Preprocessing of the 3D Model. -- 3.2 Estimation of an Intermediate Template Using BPS Neural Network -- 3.3 First Minimization: BPS to SMPL.
3.4 Second Minimization: 3D Scan to SMPL -- 4 Experiments -- 4.1 Datasets and Evaluation Metrics -- 4.2 Results -- 5 Conclusions -- References -- Lightweight Cosmetic Contact Lens Detection System for Iris Recognition at a Distance -- 1 Introduction -- 2 Related Work -- 3 Overview of the IAAD Framework -- 4 The Approach for Cosmetic Contact Lens Detection -- 4.1 BSIF Encoding of an Iris Pattern -- 4.2 Building the Ensemble of Classifiers -- 5 Results -- 5.1 Cross-Dataset Testing -- 6 Conclusions and Future Work -- References -- Vehicle Warning System Based on Road Curvature Effect Using CNN and LSTM Neural Networks -- 1 Introduction -- 2 Road Curvature-Based Dynamics of the Vehicle -- 3 Risky Maneuvers Identification by CNN and LSTM Models -- 3.1 Model's Selection of Variables -- 3.2 Deep Convolutional Neural Network Model -- 4 Results and Discussion -- 5 Conclusions and Future Works -- References -- Special Session 6: Genetic and Evolutionary Computation in Real World and Industry -- Enhancing Time Series Anomaly Detection Using Discretization and Word Embeddings -- 1 Introduction -- 2 Experimental Study -- 2.1 Problem Formulation -- 2.2 Data Preprocessing -- 2.3 Model Architecture -- 2.4 Datasets -- 3 Results -- 4 Conclusions and Future Work -- References -- Multi-objective Optimization for Multi-Robot Path Planning on Warehouse Environments -- 1 Introduction -- 2 Non-Dominated Genetic Algorithm Approach -- 2.1 Route Generation -- 2.2 Initial Population -- 2.3 Crossover -- 2.4 Mutation -- 3 Experimentation Setup -- 4 Results and Discussion -- 5 Conclusion and Future Work -- References -- On the Prediction of Anomalous Contaminant Diffusion -- 1 Introduction -- 2 Bevilacqua-Galeão (BG) Model and Numerical Solution -- 2.1 BG Model -- 2.2 Numerical Solution -- 2.3 Differential Evolution (DE) Method -- 3 Inverse Problem Formulation -- 4 Results.
4.1 Direct Problem and Case of Study.
Record Nr. UNINA-9910743693003321
García Bringas Pablo  
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Hybrid Artificial Intelligent Systems [[electronic resource] ] : 18th International Conference, HAIS 2023, Salamanca, Spain, September 5–7, 2023, Proceedings / / edited by Pablo García Bringas, Hilde Pérez García, Francisco Javier Martínez de Pisón, Francisco Martínez Álvarez, Alicia Troncoso Lora, Álvaro Herrero, José Luis Calvo Rolle, Héctor Quintián, Emilio Corchado
Hybrid Artificial Intelligent Systems [[electronic resource] ] : 18th International Conference, HAIS 2023, Salamanca, Spain, September 5–7, 2023, Proceedings / / edited by Pablo García Bringas, Hilde Pérez García, Francisco Javier Martínez de Pisón, Francisco Martínez Álvarez, Alicia Troncoso Lora, Álvaro Herrero, José Luis Calvo Rolle, Héctor Quintián, Emilio Corchado
Autore García Bringas Pablo
Edizione [1st ed. 2023.]
Pubbl/distr/stampa Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Descrizione fisica 1 online resource (789 pages)
Disciplina 006.3
Altri autori (Persone) Pérez GarcíaHilde
Martínez de PisónFrancisco Javier
Martínez ÁlvarezFrancisco
Troncoso LoraAlicia
HerreroÁlvaro
Calvo RolleJosé Luis
QuintiánHéctor
CorchadoEmilio
Collana Lecture Notes in Artificial Intelligence
Soggetto topico Artificial intelligence
Artificial Intelligence
ISBN 3-031-40725-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Anomaly and Fault Detection -- One-Class Reconstruction Methods for Categorizing DoS Attacks on CoAP -- Application of anomaly detection models to malware detection in the presence of concept drift -- Identification of anomalies in urban sound data with Autoencoders -- Revisiting Histogram Based Outlier Scores: Strengths and Weaknesses -- Data Mining and Decision Support Systems -- Model performance prediction: a Meta-Learning approach for concept drift detection -- Reinforcing Assessment Processes Using Proactive Case-Based Reasoning Mechanisms -- Meta-Learning for hyperparameters tuning in CNNs for Chest Images -- A Fuzzy Logic Ensemble Approach to Concept Drift Detection -- Multi-Task Gradient Boosting -- Exploratory Study of Data Sampling Methods for Imbalanced Legal Text Classification -- Exploring delay reduction on Edge Computing architectures from a Heuristic approach -- Probability Density Function for Clustering Validation -- Comprehensive analysis of different techniques for data augmentation and proposal of new variants of BOSME & GAN -- Multidimensional Models Supported by Document-Oriented Databases -- Financial Distress Prediction in an Imbalanced Data Stream Environment -- Improving the Quality of Quantum Services Generation Process: Controlling Errors and Noise -- Comparison of deep reinforcement learning path-following system based on road geometry and an adaptive cruise control for autonomous vehicles -- Deep Learning -- A New Hybrid CNN-LSTM for Wind Power Forecasting in Ethiopia -- Companion Classification Losses for Regression Problems -- Analysis of transformer model applications -- Real-time Workflow Scheduling in Cloud with Recursive Neural Network and List Scheduling -- Robust Losses in Deep Regression -- Structure Learning in Deep Multi-Task Models -- Validating by Deep Learning an Efficient Method for Genomic Sequence Analysis: Genomic Spectrograms -- Sentiment Analysis for Vietnamese – Based Hybrid Deep Learning Models -- Optimizing LIME explanations using REVEL Metrics -- Assessing the Impact of Noise on Quantum Neural Networks: An Experimental Analysis -- Varroa mite detection using deep learning techniques -- Evolutionary Computation and Optimization -- Enhancing Evolutionary Optimization Performance under Byzantine Fault Conditions -- A hybrid based genetic algorithm for solving the clustered generalized traveling salesman problem -- Feature Ranking for Feature Sorting and Feature Selection with Optimisation -- Efficient Simulation of Pollutant Dispersion using Machine Learning -- Hybrid Intelligent Parsimony Search in Small High-dimensional Datasets -- An integer linear programming model for team formation in the classroom with constraints -- Improved Evolutionary Approach for Tuning Topic Models with Additive Regularization -- Time of Arrival error characterization for precise indoor localization of Autonomous Ground Vehicles -- Feature Selection based on a Decision Tree Genetic Algorithm -- Exact and Heuristic Lexicographic Methods for the Fuzzy Traveling Salesman Problem -- A Novel Genetic Algorithm with Specialized Genetic Operators for Clustering -- The Analysis of Hybrid Brain Storm Optimisation Approaches in Feature Selection -- HAIS Applications -- Supporting Emotion Recognition in Human-Robot Interactions: An Experimental Italian Textual Dataset -- Hybrid Intelligent Control for Maximum Power Point Tracking of a Floating Wind Turbine -- Statistical Dialog Tracking and Management for Task-oriented Conversational Systems -- A Causally Explainable Deep Learning Model with Modular Bayesian Network for Predicting Electric Energy Demand -- Using Large Language Models for Interpreting Autonomous Robots Behaviors -- Comparative analysis of intelligent techniques for categorization of the operational status of LiFePo4 batteries -- To Enhance Full-Text Biomedical Document Classification through Semantic Enrichment -- Predicting innovative cities using spatio-temporal activity patterns -- Daily accumulative photovoltaic energy prediction using hybrid intelligent model -- Comparison of geospatial trajectory clustering and feature trajectory clustering for public transportation trip data -- Image and Speech Signal Processing -- Adapting YOLOv8 as a vision-based animal detection system to facilitate herding -- Image classification understanding with Model Inspector tool -- Study on Synthetic Video Generation of Embryo Development -- Image reconstruction using Cellular Automata and Neural Networks -- Agents and Multiagents -- Monte-Carlo Tree Search for Multi-Agent Pathfinding: Preliminary Results -- The Problem of Concept Learning and Goals of Reasoning in Large Language Models -- Multi-Agent System for Multimodal Machine Learning Object Detection -- Biomedical Applications -- Convolutional Neural Networks for Diabetic Retinopathy Grading from iPhone Fundus Images -- Risk factors and survival after premature hospital readmission in frail subjects with delirium -- Generalizing an Improved GrowCut Algorithm for Mammography Lesion Detection -- Coherence of COVID-19 mortality of Spain versus western European countries -- A Feature Selection and Association Rule Approach to Identify Genes Associated with Metastasis and Low Survival in Sarcoma -- Analysis of Frequency Bands in Electroencephalograms for Automatic Detection of Photoparoxysmal Responses -- Textural and shape features for lesion classification in mammogram analysis -- Intent Recognition using Recurrent Neural Networks on Vital Sign Data: A Machine Learning Approach.
Record Nr. UNINA-9910742491303321
García Bringas Pablo  
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Hybrid Artificial Intelligent Systems [[electronic resource] ] : 18th International Conference, HAIS 2023, Salamanca, Spain, September 5–7, 2023, Proceedings / / edited by Pablo García Bringas, Hilde Pérez García, Francisco Javier Martínez de Pisón, Francisco Martínez Álvarez, Alicia Troncoso Lora, Álvaro Herrero, José Luis Calvo Rolle, Héctor Quintián, Emilio Corchado
Hybrid Artificial Intelligent Systems [[electronic resource] ] : 18th International Conference, HAIS 2023, Salamanca, Spain, September 5–7, 2023, Proceedings / / edited by Pablo García Bringas, Hilde Pérez García, Francisco Javier Martínez de Pisón, Francisco Martínez Álvarez, Alicia Troncoso Lora, Álvaro Herrero, José Luis Calvo Rolle, Héctor Quintián, Emilio Corchado
Autore García Bringas Pablo
Edizione [1st ed. 2023.]
Pubbl/distr/stampa Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Descrizione fisica 1 online resource (789 pages)
Disciplina 006.3
Altri autori (Persone) Pérez GarcíaHilde
Martínez de PisónFrancisco Javier
Martínez ÁlvarezFrancisco
Troncoso LoraAlicia
HerreroÁlvaro
Calvo RolleJosé Luis
QuintiánHéctor
CorchadoEmilio
Collana Lecture Notes in Artificial Intelligence
Soggetto topico Artificial intelligence
Artificial Intelligence
ISBN 3-031-40725-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Anomaly and Fault Detection -- One-Class Reconstruction Methods for Categorizing DoS Attacks on CoAP -- Application of anomaly detection models to malware detection in the presence of concept drift -- Identification of anomalies in urban sound data with Autoencoders -- Revisiting Histogram Based Outlier Scores: Strengths and Weaknesses -- Data Mining and Decision Support Systems -- Model performance prediction: a Meta-Learning approach for concept drift detection -- Reinforcing Assessment Processes Using Proactive Case-Based Reasoning Mechanisms -- Meta-Learning for hyperparameters tuning in CNNs for Chest Images -- A Fuzzy Logic Ensemble Approach to Concept Drift Detection -- Multi-Task Gradient Boosting -- Exploratory Study of Data Sampling Methods for Imbalanced Legal Text Classification -- Exploring delay reduction on Edge Computing architectures from a Heuristic approach -- Probability Density Function for Clustering Validation -- Comprehensive analysis of different techniques for data augmentation and proposal of new variants of BOSME & GAN -- Multidimensional Models Supported by Document-Oriented Databases -- Financial Distress Prediction in an Imbalanced Data Stream Environment -- Improving the Quality of Quantum Services Generation Process: Controlling Errors and Noise -- Comparison of deep reinforcement learning path-following system based on road geometry and an adaptive cruise control for autonomous vehicles -- Deep Learning -- A New Hybrid CNN-LSTM for Wind Power Forecasting in Ethiopia -- Companion Classification Losses for Regression Problems -- Analysis of transformer model applications -- Real-time Workflow Scheduling in Cloud with Recursive Neural Network and List Scheduling -- Robust Losses in Deep Regression -- Structure Learning in Deep Multi-Task Models -- Validating by Deep Learning an Efficient Method for Genomic Sequence Analysis: Genomic Spectrograms -- Sentiment Analysis for Vietnamese – Based Hybrid Deep Learning Models -- Optimizing LIME explanations using REVEL Metrics -- Assessing the Impact of Noise on Quantum Neural Networks: An Experimental Analysis -- Varroa mite detection using deep learning techniques -- Evolutionary Computation and Optimization -- Enhancing Evolutionary Optimization Performance under Byzantine Fault Conditions -- A hybrid based genetic algorithm for solving the clustered generalized traveling salesman problem -- Feature Ranking for Feature Sorting and Feature Selection with Optimisation -- Efficient Simulation of Pollutant Dispersion using Machine Learning -- Hybrid Intelligent Parsimony Search in Small High-dimensional Datasets -- An integer linear programming model for team formation in the classroom with constraints -- Improved Evolutionary Approach for Tuning Topic Models with Additive Regularization -- Time of Arrival error characterization for precise indoor localization of Autonomous Ground Vehicles -- Feature Selection based on a Decision Tree Genetic Algorithm -- Exact and Heuristic Lexicographic Methods for the Fuzzy Traveling Salesman Problem -- A Novel Genetic Algorithm with Specialized Genetic Operators for Clustering -- The Analysis of Hybrid Brain Storm Optimisation Approaches in Feature Selection -- HAIS Applications -- Supporting Emotion Recognition in Human-Robot Interactions: An Experimental Italian Textual Dataset -- Hybrid Intelligent Control for Maximum Power Point Tracking of a Floating Wind Turbine -- Statistical Dialog Tracking and Management for Task-oriented Conversational Systems -- A Causally Explainable Deep Learning Model with Modular Bayesian Network for Predicting Electric Energy Demand -- Using Large Language Models for Interpreting Autonomous Robots Behaviors -- Comparative analysis of intelligent techniques for categorization of the operational status of LiFePo4 batteries -- To Enhance Full-Text Biomedical Document Classification through Semantic Enrichment -- Predicting innovative cities using spatio-temporal activity patterns -- Daily accumulative photovoltaic energy prediction using hybrid intelligent model -- Comparison of geospatial trajectory clustering and feature trajectory clustering for public transportation trip data -- Image and Speech Signal Processing -- Adapting YOLOv8 as a vision-based animal detection system to facilitate herding -- Image classification understanding with Model Inspector tool -- Study on Synthetic Video Generation of Embryo Development -- Image reconstruction using Cellular Automata and Neural Networks -- Agents and Multiagents -- Monte-Carlo Tree Search for Multi-Agent Pathfinding: Preliminary Results -- The Problem of Concept Learning and Goals of Reasoning in Large Language Models -- Multi-Agent System for Multimodal Machine Learning Object Detection -- Biomedical Applications -- Convolutional Neural Networks for Diabetic Retinopathy Grading from iPhone Fundus Images -- Risk factors and survival after premature hospital readmission in frail subjects with delirium -- Generalizing an Improved GrowCut Algorithm for Mammography Lesion Detection -- Coherence of COVID-19 mortality of Spain versus western European countries -- A Feature Selection and Association Rule Approach to Identify Genes Associated with Metastasis and Low Survival in Sarcoma -- Analysis of Frequency Bands in Electroencephalograms for Automatic Detection of Photoparoxysmal Responses -- Textural and shape features for lesion classification in mammogram analysis -- Intent Recognition using Recurrent Neural Networks on Vital Sign Data: A Machine Learning Approach.
Record Nr. UNISA-996546849803316
García Bringas Pablo  
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
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Hybrid Artificial Intelligent Systems [[electronic resource] ] : 12th International Conference, HAIS 2017, La Rioja, Spain, June 21-23, 2017, Proceedings / / edited by Francisco Javier Martínez de Pisón, Rubén Urraca, Héctor Quintián, Emilio Corchado
Hybrid Artificial Intelligent Systems [[electronic resource] ] : 12th International Conference, HAIS 2017, La Rioja, Spain, June 21-23, 2017, Proceedings / / edited by Francisco Javier Martínez de Pisón, Rubén Urraca, Héctor Quintián, Emilio Corchado
Edizione [1st ed. 2017.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017
Descrizione fisica 1 online resource (XVIII, 725 p. 248 illus.)
Disciplina 006.3
Collana Lecture Notes in Artificial Intelligence
Soggetto topico Artificial intelligence
Algorithms
Programming languages (Electronic computers)
Computer programming
Application software
Artificial Intelligence
Algorithm Analysis and Problem Complexity
Programming Languages, Compilers, Interpreters
Programming Techniques
Information Systems Applications (incl. Internet)
ISBN 3-319-59650-0
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Contents -- Data Mining, Knowledge Discovery and Big Data -- Word Embedding Based Event Detection on Social Media -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 Data Collection -- 3.2 Data Preprocessing -- 3.3 Word Embedding -- 3.4 Clustering Algorithm -- 4 Experiments and Results -- 5 Conclusion -- References -- Sentiment Analysis on TripAdvisor: Are There Inconsistencies in User Reviews? -- 1 Introduction -- 2 Sentiment Analysis -- 2.1 The Sentiment Analysis Problem -- 2.2 Sentiment Analysis Methods (SAMs) -- 3 Methodology -- 3.1 TripAdvisor -- 3.2 Web Scraping -- 3.3 Experimental Setup -- 4 Experiment Results -- 4.1 The Data Sets -- 4.2 Analysis of Results -- 5 Conclusions and Future Work -- References -- Sentiment Classification from Multi-class Imbalanced Twitter Data Using Binarization -- 1 Introduction -- 2 Proposed Classification System -- 2.1 General Overview -- 2.2 Feature Space Reduction with Multiple Correspondence Analysis -- 2.3 Balancing the Skewed Distributions -- 2.4 Weighted Classifier Combination -- 3 Feature Extraction -- 4 Experimental Study -- 4.1 Dataset -- 4.2 Set-Up -- 4.3 Results and Discussion -- 5 Conclusions and Future Works -- References -- An Ontology for Generalized Disease Incidence Detection on Twitter -- Abstract -- 1 Introduction -- 1.1 Related Work -- 2 Materials and Methods -- 2.1 An Ontology for Disease Incidence Detection on Twitter -- 2.2 Feature Extraction -- 3 The Twitter Disease Incidence Detection Pipeline -- 3.1 Corpus Generation -- 3.2 Model Training -- 3.3 Doc2Vec Tuning -- 4 Evaluation -- 4.1 Results and Discussion -- 5 Conclusion and Future Work -- References -- Hybrid Methodology Based on Bayesian Optimization and GA-PARSIMONY for Searching Parsimony Models by Combining Hyperparameter Optimization and Feature Selection -- 1 Introduction.
2 Materials and Methods -- 2.1 Extreme Gradient Boosting Machines -- 2.2 Bayesian Optimization -- 2.3 GA-PARSIMONY Methodology -- 2.4 Hybrid Method Based on Bayesian Optimization and GA-PARSIMONY -- 3 Experiments -- 3.1 Datasets and Validation Process -- 3.2 GA-PARSIMONY Settings -- 3.3 Bayesian Optimization Settings -- 3.4 Hybrid Method Settings -- 4 Results and Discussion -- 5 Conclusions -- References -- Concept Discovery in Graph Databases -- 1 Introduction -- 2 Background -- 2.1 Concept Discovery -- 2.2 Graph Databases -- 3 The Proposed Method -- 4 Experiments -- 4.1 Datasets and Experimental Setting -- 4.2 Experimental Results -- 5 Conclusion -- References -- Leveraging Distributed Representations of Elements in Triples for Predicate Linking -- 1 Introduction -- 2 Problem Definition -- 3 Related Work -- 4 Approach -- 4.1 Statistical Pattern-Based Candidate Generation -- 4.2 Similarity-Based Candidate Generation -- 4.3 Candidate Selection -- 5 Experiment -- 5.1 Dataset -- 5.2 Setting -- 5.3 Result -- 6 Conclusion -- References -- A Review of Distributed Data Models for Learning -- Abstract -- 1 Introduction -- 2 Taxonomies of Data Distribution Models -- 2.1 The Impact of Data Partitioning -- 2.2 Taxonomy Based on Data Partition -- 2.3 Taxonomy Based on Data Flow Processing -- 2.4 Taxonomy Based on the Data Cooperation Strategies -- 3 MapReduce: A Data Distribution Oriented Paradigm -- 4 New Trends in Distributed Data -- 4.1 Making the Most of In-memory Capability -- 4.2 Allowing Interprocess Communication -- 4.3 Dealing with the Drawback of Data Partitioning -- 4.4 Dealing with Data Pre-processing -- 5 Conclusions -- Acknowledgements -- References -- Bio-inspired Models and Evolutionary Computation -- Incorporating More Scaled Differences to Differential Evolution -- 1 Introduction -- 2 Methodology -- 2.1 Differential Evolution and Its Variants.
2.2 Matrix Notation for DE -- 2.3 New Variants for Differential Evolution -- 2.4 Benchmark Functions -- 3 Results and Discussion -- 4 Conclusions -- References -- Topological Evolution of Financial Network: A Genetic Algorithmic Approach -- 1 Introduction -- 2 Discrete Time Warping Genetic Algorithm (dTWGA) -- 2.1 Solution Representation -- 2.2 Mutation -- 2.3 Fitness -- 2.4 Selection -- 2.5 Iteration -- 3 Financial Network Construction -- 3.1 Minimum Spanning Tree -- 3.2 Maximum Degree Ratio -- 3.3 Spectrum -- 4 Experiment -- 5 Results and Discussion -- 6 Conclusion -- References -- Optimization of Joint Sales Potential Using Genetic Algorithm -- Abstract -- 1 Introduction -- 2 Algorithm Design -- 2.1 Initialization -- 2.2 Evaluation -- 2.3 Reproduction -- 2.4 Evolution -- 3 Testing -- 3.1 Sources of Sample Networks -- 3.2 Effects of Exploration: Guided Versus Random -- 3.3 Joint Sales Potential Optimization -- 4 Results -- 5 Discussion -- 5.1 Sparsely-Connected Networks -- 5.2 Guided or Random Exploration? -- 5.3 Number of Generations -- 5.4 Directed Networks -- 6 Conclusion -- Acknowledgement -- References -- Evolutionary Multi-objective Scheduling for Anti-Spam Filtering Throughput Optimization -- Abstract -- 1 Introduction -- 2 State of the Art -- 2.1 Throughput Optimization -- 2.2 Filter Accuracy Optimization -- 3 Problem Formulation and Proposal -- 4 Experimental Study -- 5 Results Discussion -- 6 Conclusions and Future Work -- Acknowledgements -- References -- A Hybrid Diploid Genetic Based Algorithm for Solving the Generalized Traveling Salesman Problem -- 1 Introduction -- 2 Definition of the GTSP -- 3 The Hybrid Diploid Genetic Algorithm -- 3.1 The Upper-Level (Global) Subproblem -- 3.2 The Lower-Level (Local) Subproblem -- 3.3 The Diploid Genetic Algorithm -- 4 Computational Results -- 5 Conclusions -- References.
A Novel Hybrid Nature-Inspired Scheme for Solving a Financial Optimization Problem -- Abstract -- 1 Introduction -- 2 Literature Review -- 3 Portfolio Optimization Problem -- 4 Combination of Two NII Algorithms for Portfolio Optimization -- 4.1 Differences Between Firefly and Gravitational Search Algorithm -- 5 Experimental Study -- 6 Financial Implications -- 7 Conclusions -- References -- Hypersphere Universe Boundary Method Comparison on HCLPSO and PSO -- Abstract -- 1 Introduction -- 2 Particle Swarm Optimization -- 3 Heterogeneous Comprehensive Learning Particle Swarm Optimization -- 4 Hypersphere Universe Boundary Method -- 5 Experimental Setup -- 6 Results -- 7 Results Discussion -- 8 Conclusion -- Acknowledgements -- References -- PSO with Partial Population Restart Based on Complex Network Analysis -- Abstract -- 1 Introduction -- 2 Particle Swarm Optimization (PSO) -- 3 Proposed Method -- 4 Experiment Setup -- 5 Conclusion -- Acknowledgements -- References -- Learning Algorithms -- Kernel Density-Based Pattern Classification in Blind Fasteners Installation -- 1 Introduction -- 2 Blind Fasteners Installation -- 3 Kernel Density-Based Pattern Classification Approach -- 3.1 Kernel Density Estimation for Behavioral Patterns Identification -- 3.2 Behavioral Patterns Computation -- 3.3 Distance-Based Classification -- 4 Test Scenario -- 4.1 Description of the Experimental Setup -- 4.2 Results and Discussion -- 5 Conclusions and Future Work -- References -- Training Set Fuzzification Towards Prediction Improvement -- Abstract -- 1 Introduction -- 1.1 Theoretical Background - Continuous Distributions -- 1.2 Fuzzification of Variables Using a Histogram -- 2 Sales Prediction Using Neural Networks -- 2.1 Training Set -- 2.2 Setting the Parameters of the Neural Network for Experimental Part -- 2.3 Experimental Results of a Sale Prediction.
3 Conclusion -- Acknowledgments -- References -- On the Impact of Imbalanced Data in Convolutional Neural Networks Performance -- 1 Introduction -- 2 The Imbalance Problem in Classification -- 3 Deep Learning -- 3.1 Convolutional Neural Network -- 4 Impact of Imbalanced Data on Convolutional Neural Networks -- 5 Experimentation -- 5.1 Experimental Framework -- 5.2 CNN Architecture -- 5.3 Results Analysis -- 6 Conclusions -- References -- Effectiveness of Basic and Advanced Sampling Strategies on the Classification of Imbalanced Data. A ... -- Abstract -- 1 Introduction -- 2 Related Work -- 3 Basic and Advanced Resampling Strategies -- 3.1 Basic Resampling Strategies -- 3.2 Advanced Resampling Strategies -- 4 Performance Measures -- 5 Experimental Study -- 6 Experimental Results -- 6.1 Datasets -- 6.2 Applying Resampling Strategies and Machine Learning Algorithms -- 6.3 Statistical Comparison of Classifiers Over Multiple Datasets -- 6.4 Statistical Comparison of Resampling Methods Over Multiple Datasets -- 7 Conclusions -- References -- A Perceptron Classifier, Its Correctness Proof and a Probabilistic Interpretation -- 1 Introduction -- 2 The Perceptron -- 3 Kernel Learning -- 3.1 Positive Definite Kernels -- 3.2 The Optimal Separating Hyperplane -- 3.3 The Representer Theorem, See [18] -- 4 Correctness Proof of the Modified Pocket Algorithm -- 5 Probabilistic Interpretation of the Decision Procedure -- 6 Conclusion and Outlook -- References -- Parallel Implementation of a Simplified Semi-physical Wildland Fire Spread Model Using OpenMP -- 1 Introduction -- 2 The Model -- 3 Parallel Model Implementation -- 4 Experiments and Results -- 4.1 Real Case Study -- 4.2 Performance Analysis/Evaluation -- 5 Conclusions and Further Research -- References -- A Study on the Noise Label Influence in Boosting Algorithms: AdaBoost, GBM and XGBoost -- 1 Introduction.
2 Class Noise. Preprocessing vs. Robust Methods.
Record Nr. UNISA-996466273803316
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Hybrid Artificial Intelligent Systems : 12th International Conference, HAIS 2017, La Rioja, Spain, June 21-23, 2017, Proceedings / / edited by Francisco Javier Martínez de Pisón, Rubén Urraca, Héctor Quintián, Emilio Corchado
Hybrid Artificial Intelligent Systems : 12th International Conference, HAIS 2017, La Rioja, Spain, June 21-23, 2017, Proceedings / / edited by Francisco Javier Martínez de Pisón, Rubén Urraca, Héctor Quintián, Emilio Corchado
Edizione [1st ed. 2017.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017
Descrizione fisica 1 online resource (XVIII, 725 p. 248 illus.)
Disciplina 006.3
Collana Lecture Notes in Artificial Intelligence
Soggetto topico Artificial intelligence
Algorithms
Programming languages (Electronic computers)
Computer programming
Application software
Artificial Intelligence
Algorithm Analysis and Problem Complexity
Programming Languages, Compilers, Interpreters
Programming Techniques
Information Systems Applications (incl. Internet)
ISBN 3-319-59650-0
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Contents -- Data Mining, Knowledge Discovery and Big Data -- Word Embedding Based Event Detection on Social Media -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 Data Collection -- 3.2 Data Preprocessing -- 3.3 Word Embedding -- 3.4 Clustering Algorithm -- 4 Experiments and Results -- 5 Conclusion -- References -- Sentiment Analysis on TripAdvisor: Are There Inconsistencies in User Reviews? -- 1 Introduction -- 2 Sentiment Analysis -- 2.1 The Sentiment Analysis Problem -- 2.2 Sentiment Analysis Methods (SAMs) -- 3 Methodology -- 3.1 TripAdvisor -- 3.2 Web Scraping -- 3.3 Experimental Setup -- 4 Experiment Results -- 4.1 The Data Sets -- 4.2 Analysis of Results -- 5 Conclusions and Future Work -- References -- Sentiment Classification from Multi-class Imbalanced Twitter Data Using Binarization -- 1 Introduction -- 2 Proposed Classification System -- 2.1 General Overview -- 2.2 Feature Space Reduction with Multiple Correspondence Analysis -- 2.3 Balancing the Skewed Distributions -- 2.4 Weighted Classifier Combination -- 3 Feature Extraction -- 4 Experimental Study -- 4.1 Dataset -- 4.2 Set-Up -- 4.3 Results and Discussion -- 5 Conclusions and Future Works -- References -- An Ontology for Generalized Disease Incidence Detection on Twitter -- Abstract -- 1 Introduction -- 1.1 Related Work -- 2 Materials and Methods -- 2.1 An Ontology for Disease Incidence Detection on Twitter -- 2.2 Feature Extraction -- 3 The Twitter Disease Incidence Detection Pipeline -- 3.1 Corpus Generation -- 3.2 Model Training -- 3.3 Doc2Vec Tuning -- 4 Evaluation -- 4.1 Results and Discussion -- 5 Conclusion and Future Work -- References -- Hybrid Methodology Based on Bayesian Optimization and GA-PARSIMONY for Searching Parsimony Models by Combining Hyperparameter Optimization and Feature Selection -- 1 Introduction.
2 Materials and Methods -- 2.1 Extreme Gradient Boosting Machines -- 2.2 Bayesian Optimization -- 2.3 GA-PARSIMONY Methodology -- 2.4 Hybrid Method Based on Bayesian Optimization and GA-PARSIMONY -- 3 Experiments -- 3.1 Datasets and Validation Process -- 3.2 GA-PARSIMONY Settings -- 3.3 Bayesian Optimization Settings -- 3.4 Hybrid Method Settings -- 4 Results and Discussion -- 5 Conclusions -- References -- Concept Discovery in Graph Databases -- 1 Introduction -- 2 Background -- 2.1 Concept Discovery -- 2.2 Graph Databases -- 3 The Proposed Method -- 4 Experiments -- 4.1 Datasets and Experimental Setting -- 4.2 Experimental Results -- 5 Conclusion -- References -- Leveraging Distributed Representations of Elements in Triples for Predicate Linking -- 1 Introduction -- 2 Problem Definition -- 3 Related Work -- 4 Approach -- 4.1 Statistical Pattern-Based Candidate Generation -- 4.2 Similarity-Based Candidate Generation -- 4.3 Candidate Selection -- 5 Experiment -- 5.1 Dataset -- 5.2 Setting -- 5.3 Result -- 6 Conclusion -- References -- A Review of Distributed Data Models for Learning -- Abstract -- 1 Introduction -- 2 Taxonomies of Data Distribution Models -- 2.1 The Impact of Data Partitioning -- 2.2 Taxonomy Based on Data Partition -- 2.3 Taxonomy Based on Data Flow Processing -- 2.4 Taxonomy Based on the Data Cooperation Strategies -- 3 MapReduce: A Data Distribution Oriented Paradigm -- 4 New Trends in Distributed Data -- 4.1 Making the Most of In-memory Capability -- 4.2 Allowing Interprocess Communication -- 4.3 Dealing with the Drawback of Data Partitioning -- 4.4 Dealing with Data Pre-processing -- 5 Conclusions -- Acknowledgements -- References -- Bio-inspired Models and Evolutionary Computation -- Incorporating More Scaled Differences to Differential Evolution -- 1 Introduction -- 2 Methodology -- 2.1 Differential Evolution and Its Variants.
2.2 Matrix Notation for DE -- 2.3 New Variants for Differential Evolution -- 2.4 Benchmark Functions -- 3 Results and Discussion -- 4 Conclusions -- References -- Topological Evolution of Financial Network: A Genetic Algorithmic Approach -- 1 Introduction -- 2 Discrete Time Warping Genetic Algorithm (dTWGA) -- 2.1 Solution Representation -- 2.2 Mutation -- 2.3 Fitness -- 2.4 Selection -- 2.5 Iteration -- 3 Financial Network Construction -- 3.1 Minimum Spanning Tree -- 3.2 Maximum Degree Ratio -- 3.3 Spectrum -- 4 Experiment -- 5 Results and Discussion -- 6 Conclusion -- References -- Optimization of Joint Sales Potential Using Genetic Algorithm -- Abstract -- 1 Introduction -- 2 Algorithm Design -- 2.1 Initialization -- 2.2 Evaluation -- 2.3 Reproduction -- 2.4 Evolution -- 3 Testing -- 3.1 Sources of Sample Networks -- 3.2 Effects of Exploration: Guided Versus Random -- 3.3 Joint Sales Potential Optimization -- 4 Results -- 5 Discussion -- 5.1 Sparsely-Connected Networks -- 5.2 Guided or Random Exploration? -- 5.3 Number of Generations -- 5.4 Directed Networks -- 6 Conclusion -- Acknowledgement -- References -- Evolutionary Multi-objective Scheduling for Anti-Spam Filtering Throughput Optimization -- Abstract -- 1 Introduction -- 2 State of the Art -- 2.1 Throughput Optimization -- 2.2 Filter Accuracy Optimization -- 3 Problem Formulation and Proposal -- 4 Experimental Study -- 5 Results Discussion -- 6 Conclusions and Future Work -- Acknowledgements -- References -- A Hybrid Diploid Genetic Based Algorithm for Solving the Generalized Traveling Salesman Problem -- 1 Introduction -- 2 Definition of the GTSP -- 3 The Hybrid Diploid Genetic Algorithm -- 3.1 The Upper-Level (Global) Subproblem -- 3.2 The Lower-Level (Local) Subproblem -- 3.3 The Diploid Genetic Algorithm -- 4 Computational Results -- 5 Conclusions -- References.
A Novel Hybrid Nature-Inspired Scheme for Solving a Financial Optimization Problem -- Abstract -- 1 Introduction -- 2 Literature Review -- 3 Portfolio Optimization Problem -- 4 Combination of Two NII Algorithms for Portfolio Optimization -- 4.1 Differences Between Firefly and Gravitational Search Algorithm -- 5 Experimental Study -- 6 Financial Implications -- 7 Conclusions -- References -- Hypersphere Universe Boundary Method Comparison on HCLPSO and PSO -- Abstract -- 1 Introduction -- 2 Particle Swarm Optimization -- 3 Heterogeneous Comprehensive Learning Particle Swarm Optimization -- 4 Hypersphere Universe Boundary Method -- 5 Experimental Setup -- 6 Results -- 7 Results Discussion -- 8 Conclusion -- Acknowledgements -- References -- PSO with Partial Population Restart Based on Complex Network Analysis -- Abstract -- 1 Introduction -- 2 Particle Swarm Optimization (PSO) -- 3 Proposed Method -- 4 Experiment Setup -- 5 Conclusion -- Acknowledgements -- References -- Learning Algorithms -- Kernel Density-Based Pattern Classification in Blind Fasteners Installation -- 1 Introduction -- 2 Blind Fasteners Installation -- 3 Kernel Density-Based Pattern Classification Approach -- 3.1 Kernel Density Estimation for Behavioral Patterns Identification -- 3.2 Behavioral Patterns Computation -- 3.3 Distance-Based Classification -- 4 Test Scenario -- 4.1 Description of the Experimental Setup -- 4.2 Results and Discussion -- 5 Conclusions and Future Work -- References -- Training Set Fuzzification Towards Prediction Improvement -- Abstract -- 1 Introduction -- 1.1 Theoretical Background - Continuous Distributions -- 1.2 Fuzzification of Variables Using a Histogram -- 2 Sales Prediction Using Neural Networks -- 2.1 Training Set -- 2.2 Setting the Parameters of the Neural Network for Experimental Part -- 2.3 Experimental Results of a Sale Prediction.
3 Conclusion -- Acknowledgments -- References -- On the Impact of Imbalanced Data in Convolutional Neural Networks Performance -- 1 Introduction -- 2 The Imbalance Problem in Classification -- 3 Deep Learning -- 3.1 Convolutional Neural Network -- 4 Impact of Imbalanced Data on Convolutional Neural Networks -- 5 Experimentation -- 5.1 Experimental Framework -- 5.2 CNN Architecture -- 5.3 Results Analysis -- 6 Conclusions -- References -- Effectiveness of Basic and Advanced Sampling Strategies on the Classification of Imbalanced Data. A ... -- Abstract -- 1 Introduction -- 2 Related Work -- 3 Basic and Advanced Resampling Strategies -- 3.1 Basic Resampling Strategies -- 3.2 Advanced Resampling Strategies -- 4 Performance Measures -- 5 Experimental Study -- 6 Experimental Results -- 6.1 Datasets -- 6.2 Applying Resampling Strategies and Machine Learning Algorithms -- 6.3 Statistical Comparison of Classifiers Over Multiple Datasets -- 6.4 Statistical Comparison of Resampling Methods Over Multiple Datasets -- 7 Conclusions -- References -- A Perceptron Classifier, Its Correctness Proof and a Probabilistic Interpretation -- 1 Introduction -- 2 The Perceptron -- 3 Kernel Learning -- 3.1 Positive Definite Kernels -- 3.2 The Optimal Separating Hyperplane -- 3.3 The Representer Theorem, See [18] -- 4 Correctness Proof of the Modified Pocket Algorithm -- 5 Probabilistic Interpretation of the Decision Procedure -- 6 Conclusion and Outlook -- References -- Parallel Implementation of a Simplified Semi-physical Wildland Fire Spread Model Using OpenMP -- 1 Introduction -- 2 The Model -- 3 Parallel Model Implementation -- 4 Experiments and Results -- 4.1 Real Case Study -- 4.2 Performance Analysis/Evaluation -- 5 Conclusions and Further Research -- References -- A Study on the Noise Label Influence in Boosting Algorithms: AdaBoost, GBM and XGBoost -- 1 Introduction.
2 Class Noise. Preprocessing vs. Robust Methods.
Record Nr. UNINA-9910484314803321
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017
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International Joint Conference 16th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2023) 14th International Conference on EUropean Transnational Education (ICEUTE 2023) [[electronic resource] ] : Proceedings / / edited by Pablo García Bringas, Hilde Pérez García, Francisco Javier Martínez de Pisón, Francisco Martínez Álvarez, Alicia Troncoso Lora, Álvaro Herrero, José Luis Calvo Rolle, Héctor Quintián, Emilio Corchado
International Joint Conference 16th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2023) 14th International Conference on EUropean Transnational Education (ICEUTE 2023) [[electronic resource] ] : Proceedings / / edited by Pablo García Bringas, Hilde Pérez García, Francisco Javier Martínez de Pisón, Francisco Martínez Álvarez, Alicia Troncoso Lora, Álvaro Herrero, José Luis Calvo Rolle, Héctor Quintián, Emilio Corchado
Autore García Bringas Pablo
Edizione [1st ed. 2023.]
Pubbl/distr/stampa Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Descrizione fisica 1 online resource (377 pages)
Disciplina 006.3
Altri autori (Persone) Pérez GarcíaHilde
Martínez de PisónFrancisco Javier
Martínez ÁlvarezFrancisco
Troncoso LoraAlicia
HerreroÁlvaro
Calvo RolleJosé Luis
QuintiánHéctor
CorchadoEmilio
Collana Lecture Notes in Networks and Systems
Soggetto topico Computational intelligence
Engineering - Data processing
Education
Computational Intelligence
Data Engineering
ISBN 3-031-42519-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Finding and removing infected T -trees in IoT networks -- Intrusion Detection and Prevention in Industrial Internet of Things: A Study -- Critical analysis of global models for malware propagation on wireless sensor networks -- A novel method for failure detection based on real-time systems identification -- Accountability & explainability in robotics: a proof of concept for ROS 2- and Nav2-based mobile robots -- Reducing the security margin against a differential attack in the TinyJambu cryptosystem -- Analysis of extractive text summarization methods as a binary classification problem -- Systematic literature review of methods used for SQL injection detection based on intelligent algorithms -- Benchmarking Classifiers for DDoS Attack Detection in Industrial IoT Networks -- Impact of the Keep-Alive Parameter on SQL Injection Attack Detection in Network Flow Data -- QuantumSolver Composer: Automatic Quantum Transformation of Classical Circuits.
Record Nr. UNINA-9910742494903321
García Bringas Pablo  
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui