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[null,null,"Titolo",null,"17th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2022) : Salamanca, Spain, September 5–7, 2022, Proceedings / / edited by Pablo García Bringas, Hilde Pérez García, Francisco Javier Martinez-de-Pison, José Ramón Villar Flecha, Alicia Troncoso Lora, Enrique A. de la Cal, Álvaro Herrero, Francisco Martínez Álvarez, Giuseppe Psaila, Héctor Quintián, Emilio S. Corchado Rodriguez"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023"]
[null,null,"ISBN",null,"3-031-18050-X"]
[null,null,"Edizione",null,"[1st ed. 2023.]"]
[null,null,"Descrizione fisica",null,"1 online resource (676 pages)"]
[null,null,"Collana",null,"Lecture Notes in Networks and Systems, , 2367-3389 ; ; 531"]
[null,null,"Disciplina",null,"929.605"]
[null,null,"Soggetti",null,"Computational intelligence"]
[{"$nulls":4},"Industrial engineering"]
[{"$nulls":4},"Production engineering"]
[{"$nulls":4},"Computational Intelligence"]
[{"$nulls":4},"Industrial and Production Engineering"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"Intro -- Preface -- Organization -- General Chair -- International Advisory Committee -- Program Committee Chairs -- Program Committee -- Special Sessions -- Machine Learning and Computer Vision in Industry 4.0 -- Program Committee -- Time Series Forecasting in Industrial and Environmental Applications -- Program Committee -- Optimization, Modeling, and Control by Soft Computing Techniques -- Program Committee -- Soft Computing Applied to Renewable Energy Systems -- Program Committee -- Preprocessing Big Data in Machine Learning -- Program Committee -- Tackling Real-World Problems with Artificial Intelligence -- Program Committee -- SOCO 2022 Organizing Committee Chairs -- SOCO 2022 Organizing Committee -- Contents -- Decision Support and Deep Learning -- Anomaly Detection of Security Threats to Cyber-Physical Systems: A Study -- 1 Introduction -- 2 Statistical Analysis -- 3 Literature Analysis -- 3.1 CPS Security Design -- 3.2 Anomaly Detection/Threat Detection in CPS -- 4 Outstanding Challenges -- 5 Conclusions -- References -- Predictive Maintenance for Maintenance-Effective "]
[{"$nulls":4},"Manufacturing Using Machine Learning Approaches -- 1 Introduction -- 2 State-of-the-Art -- 3 Training/Testing Dataset -- 4 Proposed Methodology -- 4.1 Gradient Boosting Training -- 4.2 Support Vector Machine Training -- 5 Results and Discussion -- 6 Conclusions -- References -- Estimation of Lamb Weight Using Transfer Learning and Regression -- 1 Introduction -- 2 Image Acquisition and Data Preparation -- 3 Proposed Architecture -- 4 Experimental Results -- 5 Conclusions -- References -- UAV Simulation for Object Detection and 3D Reconstruction Fusing 2D LiDAR and Camera -- 1 Introduction -- 2 Related Works -- 3 Simulation Framework -- 4 Proposed Process -- 5 Demonstration and Evaluation -- 6 Conclusions and Perspectives -- References."]
[{"$nulls":4},"A SO2 Pollution Concentrations Prediction Approach Using Autoencoders -- 1 Introduction -- 2 Database -- 3 Methodology -- 4 Results -- 5 Conclusions -- References -- CPU Computation Influence on Energy Consumption Forecasting Activities of a Building -- 1 Introduction -- 2 Methodology -- 3 Case Study and Results -- 3.1 Case Study -- 3.2 Results -- 4 Conclusions -- References -- Python-Based Ecosystem for Agent Communities Simulation -- 1 Introduction -- 2 Related Works -- 3 Proposed Solution -- 3.1 PEAK Multi-agent System Platform -- 3.2 Management -- 4 Case Study -- 5 Conclusion -- References -- Deep Learning Approach for the Prediction of the Concentration of Chlorophyll ɑ in Seawater. A Case Study in El Mar Menor (Spain) -- 1 Introduction -- 2 Area Description and Datasets -- 3 Methods -- 3.1 Artificial Neural Networks -- 3.2 Bayesian Regularized Neural Networks -- 3.3 Long Short-Term Memory Neural Networks -- 3.4 Mutual Information -- 3.5 Minimum-Redundancy-Maximum-Relevance (mRMR) -- 4 Experimental Procedure -- 4.1 Creation of the Lagged Datasets -- 4.2 Forecasting Models -- 5 Results and Discussion -- 6 Conclusions -- References -- Evolutionary Computing -- A Hybrid Discrete Symbiotic Organisms Search Algorithm and List-Based Simulated Annealing Algorithm for Traveling Salesman Problem -- 1 Introduction -- 2 A Discrete Symbiotic Organisms Search Algorithm for TSP -- 2.1 Mutualism Phase -- 2.2 Commensalism Phase -- 2.3 Parasitism Phase -- 3 A List-Based Simulated Annealing Algorithm for TSP -- 4 A Hybrid DSOS-LBSA Algorithm for TSP -- 5 Computational Results and Discussion -- 5.1 Parameter Settings -- 5.2 Computational Results and Analysis -- 6 Conclusion and Future Work -- References -- Estimation of Distribution Algorithms Applied to the Next Release Problem -- 1 Introduction -- 2 Next Release Problem -- 2.1 Related Work."]
[{"$nulls":4},"2.2 Multi-objective Next Release Problem -- 3 Proposal: Univariate EDAs for the MONRP -- 3.1 MONRP-UMDA -- 3.2 MONRP-PBIL -- 4 Experimental Evaluation -- 4.1 Algorithms -- 4.2 Datasets -- 4.3 Methodology -- 5 Results and Analysis -- 5.1 Best Configurations -- 5.2 Pareto Front Results -- 5.3 Metrics Results -- 6 Conclusions and Future Works -- References -- An Extremal Optimization Approach to the Pairwise Connectivity Critical Node Detection Problem -- 1 Introduction -- 2 Related Work and Problem Formulation -- 3 Extremal Optimization -- 4 Numerical Experiments -- 5 Conclusions -- References -- Neural Networks and Data Mining -- Dimensional Reduction Applied to an Intelligent Model for Boost Converter Switching Operation -- 1 Introduction -- 2 Case Study -- 3 Model Approach -- 3.1 Dataset -- 3.2 Methods -- 3.3 Classification Model -- 3.4 Experiments Description -- 4 Results -- 5 Conclusions and Future Works -- References -- Intuitionistic Fuzzy Sets in J-CO-QL+? -- 1 Introduction -- 2 Background -- 2.1 Classical Fuzzy Sets -- 2.2 Intuitionistic Fuzzy Sets and Relations -- 2.3 Example: Representing "]
[{"$nulls":4},"Medical Knowledge -- 3 Intuitionistic Fuzzy Sets and J-CO-QL+ -- 3.1 J-CO-QL+ Data Model and Execution Model -- 3.2 J-CO-QL+ Script -- 4 Learned Lessons and Conclusions -- References -- Assessing the Efficient Market Hypothesis for Cryptocurrencies with High-Frequency Data Using Time Series Classification -- 1 Introduction -- 2 Literature Review -- 3 Methods -- 4 Experiments and Results -- 4.1 Datasets Used -- 4.2 Experimental Settings and Performance Measures -- 4.3 Results -- 5 Conclusions -- References -- Blockchain for Supply Chain Traceability with Data Validation -- 1 Introduction -- 2 Related Work -- 3 Blockchain-Based GSC Traceability -- 4 Smart Contract for GSC Traceability -- 5 Smart Contract Implementation and Performance Evaluation."]
[{"$nulls":4},"6 Conclusions and Future Work -- References -- Compression of Clustered Ship Trajectories for Context Learning and Anomaly Detection -- 1 Introduction -- 2 Background Information -- 2.1 Data Pre-processing and Data Imbalance -- 2.2 Trajectory Clustering -- 2.3 Trajectory Compression -- 3 Proposed Architecture -- 3.1 Data Preparation and Cluster Generation -- 3.2 Compression of Trajectories -- 3.3 Representative Points Extraction -- 4 Results Analysis -- 5 Conclusions and Perspectives -- References -- DR Participants' Actual Response Prediction Using Artificial Neural Networks -- 1 Introduction -- 2 Proposed Methodology -- 3 Case Study -- 4 Results and Discussion -- 5 Conclusion -- References -- Non-linear Neural Models to Predict HRC Steel Price in Spain -- 1 Introduction and Previous Work -- 2 Materials and Methods -- 2.1 Dataset -- 2.2 Non-lineal Neural Models -- 3 Experiments and Results -- 4 Conclusions and Future Work -- References -- Soft Computing Applications -- First Steps Predicting Execution of Civil Works from Georeferenced Infrastructure Data -- 1 Introduction -- 1.1 State of the Art -- 1.2 Research Proposal -- 2 Methodology -- 2.1 Preprocess -- 2.2 Data Analysis -- 2.3 Dataset Generation -- 2.4 Supervised Classification -- 2.5 Evaluation -- 2.6 Results -- 3 Conclusion -- References -- Virtual Sensor to Estimate Air Pollution Heavy Metals Using Bioindicators -- 1 Introduction -- 2 Database -- 3 Methodology -- 4 Results -- 5 Conclusions -- References -- Regression Techniques to Predict the Growth of Potato Tubers -- 1 Introduction -- 2 Previous Work -- 3 Regression Techniques -- 3.1 Multiple Linear Regression -- 3.2 Multilayer Perceptron -- 3.3 Radial-Basis Function Network -- 3.4 Support Vector Machine -- 4 Materials and Methods -- 5 Results and Discussion -- 6 Conclusions and Future Work -- References."]
[{"$nulls":4},"Reliability-Sensitive Optimization for Provision of Ancillary Services by Tempo-Spatial Correlated Distributed Energy Resources -- 1 Introduction -- 2 Multivariate Correlation Modeling -- 2.1 Pair-Copula Construction -- 2.2 D-Vine Copula Structure -- 3 Reliability-Sensitive Optimization -- 3.1 Multivariate Correlation Modeling -- 3.2 Joint Reliability Evaluation Methodology -- 4 Simulation Study -- 5 Conclusion -- References -- Special Session on Machine Learning and Computer Vision in Industry 4.0 -- Predictive Maintenance of ATM Machines by Modelling Remaining Useful Life with Machine Learning Techniques -- 1 Introduction -- 2 Materials -- 3 Methods -- 3.1 Task Definition -- 3.2 Feature Extraction and Selection -- 3.3 Pre-processing -- 3.4 Machine Learning Model -- 3.5 Experimental Procedure -- 4 Results -- 5 PdM Decision Support System for SIMPLE Project -- 6 Conclusions -- References -- The Impact of Content Deletion on Tabular Data Similarity Using Contextual Word Embeddings -- 1 Introduction -- 2 Related Work -- 3 Research Method -- 4 Experiments -- 4.1 Models -- 4.2 Datasets -- 4.3 Results -- 5 Conclusions and Future Work -- References -- Deep Learning-Based "]
[{"$nulls":4},"Dementia Prediction Using Multimodal Data -- 1 Introduction -- 2 DementiaBank Dataset -- 3 Approach -- 3.1 Audio -- 3.2 Text -- 3.3 Multimodal -- 3.4 Other Approaches -- 4 Evaluation -- 5 Conclusion -- References -- Lightweight Models in Face Attribute Recognition: Performance Under Oclussions -- 1 Introduction -- 2 Related Work -- 3 Description of the System -- 3.1 Models -- 3.2 Datasets -- 4 Experimental Setup -- 4.1 Training -- 4.2 Evaluation -- 5 Evaluation with Masked Faces -- 6 Conclusions and Future Work -- References -- Small Vessel Detection in Changing Seaborne Environments Using Anchor-Free Detectors on Aerial Images -- 1 Introduction -- 2 Related Work -- 2.1 Vessel Detection."]
[{"$nulls":4},"2.2 Datasets."]
[null,null,null,"Sommario/riassunto","This book contains accepted papers presented at SOCO 2022 conference held in the beautiful and historic city of Salamanca (Spain), in September 2022. Soft computing represents a collection or set of computational techniques in machine learning, computer science, and some engineering disciplines, which investigate, simulate, and analyze very complex issues and phenomena. After a thorough peer-review process, the 17th SOCO 2022 International Program Committee selected 64 papers which are published in these conference proceedings and represent an acceptance rate of 60%. In this relevant edition, a particular emphasis was put on the organization of special sessions. Seven special sessions were organized related to relevant topics such as machine learning and computer vision in Industry 4.0; time series forecasting in industrial and environmental applications; optimization, modeling, and control by soft computing techniques; soft computing applied to renewable energy systems; preprocessing big data in machine learning; tackling real-world problems with artificial intelligence. The selection of papers was extremely rigorous to maintain the high quality of the conference. We want to thank the members of the program committees for their hard work during the reviewing process. This is a crucial process for creating a high-standard conference; the SOCO conference would not exist without their help."]