LEADER 13364nam 22006255 450 001 9910743701003321 005 20250626164240.0 010 $a3-031-42529-4 024 7 $a10.1007/978-3-031-42529-5 035 $a(MiAaPQ)EBC30724527 035 $a(Au-PeEL)EBL30724527 035 $a(DE-He213)978-3-031-42529-5 035 $a(PPN)272266132 035 $a(CKB)28112527300041 035 $a(EXLCZ)9928112527300041 100 $a20230830d2023 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$a18th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2023) $eSalamanca, Spain, September 5?7, 2023, Proceedings, Volume 1 /$fedited 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 205 $a1st ed. 2023. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2023. 215 $a1 online resource (305 pages) 225 1 $aLecture Notes in Networks and Systems,$x2367-3389 ;$v749 300 $aIncludes index. 311 08$aPrint version: García Bringas, Pablo 18th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2023) Cham : Springer,c2023 9783031425288 327 $aIntro -- 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. 327 $a4.2 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. 327 $aTinyNARM: 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. 327 $a6 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. 327 $aNeuroevolutionary 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. 327 $a2 Related Literature. 330 $aThis book of Advances in Intelligent and Soft Computing contains accepted papers presented at SOCO 2023 conference held in the beautiful and historic city of Salamanca (Spain) in September 2023. Soft computing represents a collection or set of computational techniques in machine learning, computer science, and some engineering disciplines, which investigate, simulate, and analyze very complex issues and phenomena. After a through peer-review process, the 18th SOCO 2023 International Program Committee selected 61 papers which are published in these conference proceedings and represents an acceptance rate of 60%. In this relevant edition, a particular emphasis was put on the organization of special sessions. Seven special sessions were organized related to relevant topics such as: Time Series Forecasting in Industrial and Environmental Applications, Technological Foundations and Advanced Applications of Drone Systems, Soft Computing Methods in Manufacturing and Management Systems, Efficiency and Explainability in Machine Learning and Soft Computing, Machine Learning and Computer Vision in Industry 4.0, Genetic and Evolutionary Computation in Real World and Industry, and Soft Computing and Hard Computing for a Data Science Process Model. The selection of papers was extremely rigorous to maintain the high quality of the conference. We want to thank the members of the Program Committees for their hard work during the reviewing process. This is a crucial process for creating a high-standard conference; the SOCO conference would not exist without their help. 410 0$aLecture Notes in Networks and Systems,$x2367-3389 ;$v749 606 $aComputational intelligence 606 $aIndustrial engineering 606 $aProduction engineering 606 $aComputational Intelligence 606 $aIndustrial and Production Engineering 615 0$aComputational intelligence. 615 0$aIndustrial engineering. 615 0$aProduction engineering. 615 14$aComputational Intelligence. 615 24$aIndustrial and Production Engineering. 676 $a006.3 702 $aGarci?a Bringas$b Pablo 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910743701003321 996 $a18th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2023)$94240936 997 $aUNINA LEADER 09837nam 22007815 450 001 9910552712003321 005 20251113202736.0 010 $a3-030-97549-5 024 7 $a10.1007/978-3-030-97549-4 035 $a(MiAaPQ)EBC6930896 035 $a(Au-PeEL)EBL6930896 035 $a(CKB)21403916800041 035 $a(PPN)261518046 035 $a(OCoLC)1305016219 035 $a(DE-He213)978-3-030-97549-4 035 $a(EXLCZ)9921403916800041 100 $a20220317d2022 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aLarge-Scale Scientific Computing $e13th International Conference, LSSC 2021, Sozopol, Bulgaria, June 7?11, 2021, Revised Selected Papers /$fedited by Ivan Lirkov, Svetozar Margenov 205 $a1st ed. 2022. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2022. 215 $a1 online resource (557 pages) 225 1 $aLecture Notes in Computer Science,$x1611-3349 ;$v13127 311 08$aPrint version: Lirkov, Ivan Large-Scale Scientific Computing Cham : Springer International Publishing AG,c2022 9783030975487 327 $aInvited Papers -- Random-walk Based Approximate k-Nearest Neighbors Algorithm for Diffusion State Distance -- Model Reduction for Large Scale Systems -- II Fractional Di_usion Problems: Numerical Methods, Algorithms and Applications -- Constructions of Second Order Approximations of the Caputo Fractional Derivative -- Parameter Identification Approach for a Fractional Dynamics Model of Honeybee Population -- A Newton?s Method for Best Uniform Polynomial Approximation -- Reduced Sum Implementation of the BURA Method for Spectral Fractional Diffusion Problems -- First-order Reaction-diffusion System with Space-fractional Diffusion in an Unbounded medium -- Performance Study of Hierarchical Semi-Separable Compression Solver for Parabolic Problems with Space-fractional Diffusion -- Numerical Solution of Non-Stationary Problems with a Rational Approximation for Fractional Powers of the Operator -- Large-Scale Models: Numerical Methods, Parallel Computations and Applications -- An Exact Schur ComplementMethod for Time-harmonic Optimal Control Problems -- On the Consistency Order of Runge?Kutta Methods Combined with Active Richardson Extrapolation -- Study the Recurrence of the Dominant Pollutants in the Formation of AQI Status Over the City of Sofia for the Period 2013-2020 -- One Solution of Task with Internal Flow in Non-uniform Fluid Using CABARET Method -- Behavior and Scalability of the Regional Climate Model RegCM4 on High Performance Computing Platforms -- Quantum Effects on 1/2[111] Edge Dislocation Motion in Hydrogen-Charged Fe from Ring-Polymer Molecular Dynamics -- Degeneracy of Tetrahedral Partitions Produced by Randomly Generated Red Refinements -- Effluent Recirculation for Contaminant Removal in Constructed Wetlands under Uncertainty: A Stochastic Numerical Approach Based on Monte Carlo Methodology -- Sensitivity Study of Large-Scale Air Pollution Model Based on Modifications of the Latin Hypercube Sampling Method -- Sensitivity Operator-Based Approach to the Interpretation ofHeterogeneous Air Quality Monitoring Data -- Using the Cauchy Criterion and the Standard Deviation to Evaluate the Sustainability of Climate Simulations -- Multidimensional Sensitivity Analysis of an Air Pollution Model Based on Modifications of the van der Corput Sequence -- Running an Atmospheric Chemistry Scheme from a Large Air Pollution Model by Using Advanced Versions of the Richardson Extrapolation -- Application of Metaheuristics to Large-Scale Problems -- New Clustering Techniques of Node Embeddings Based on Metaheuristic Optimization Algorithms -- A Comparison of Machine Learning Methods for Forecasting Dow Jones Stock Index -- Optimal Knockout Tournaments: Definition and Computation -- Risk Registry Platform for Optimizations in Cases of CBRN and Critical Infrastructure Attacks -- Influence of the ACO Evaporation Parameter for Unstructured Workforce Planning Problem -- binMeta: a New Java Package for Meta-heuristic Searches -- Synergy between Convergence and Divergence ? Review of Concepts and Methods -- Advanced Stochastic Approaches Based on Optimization of Lattice Sequences for Large-Scale Finance Problems -- Intuitionistic Fuzzy Approach for Outsourcing Provider Selection in a Refinery -- Quantitative Relationship Between Particulate Matter and Morbidity -- Advanced Discretizations and Solvers for Coupled Systems of Partial Differential Equations -- Decoupling Methods for Systems of Parabolic Equations -- Optimal Control of ODEs, PDEs and Applications -- Random Lifting of Set-valued Maps -- Höolder Regularity in Bang-Bang Type Affine Optimal Control Problems -- Simultaneous Space-time Finite Element Methods for Parabolic Optimal Control Problems -- A New Algorithm for the LQR Problem with Partially Unknown Dynamics -- Tensor and Matrix Factorization for Big-Data Analysis -- Solving Systems of Polynomial Equations ? a Tensor Approach -- Nonnegative Tensor-train Low-rank Approximations of the Smoluchowski Coagulation Equation -- Boolean Hierarchical Tucker Networks on Quantum Annealers -- Topic Analysis of Superconductivity Literature by Semantic Non-negative Matrix Factorization -- Machine Learning and Model Order Reduction for Large Scale Predictive Simulations -- Deep Neural Networks and Adaptive Quadrature for Solving Variational Problems -- A full order, reduced order and machine learning model pipeline for efficient prediction of reactive flows -- A Multiscale Fatigue Model for the Degradation of Fiber-reinforced Materials -- A Classification Algorithm for Anomaly Detection in Terahertz Tomography -- Reduced Basis Methods for Efficient Simulation of a Rigid Robot Hand Interacting with Soft Tissue -- Structured Deep Kernel Networks for Data-Driven Closure Terms of Turbulent Flows -- HPC and Big Data: Algorithms and Applications -- On the Use of Low-discrepancy Sequences in the Training of Neural Networks -- A PGAS-based Implementation for the Parallel Minimum Spanning Tree Algorithm -- Comparison of Di_erent Methods for Multiple Imputation by Chain Equation -- Monte Carlo Method for Estimating Eigenvalues Using Error Balancing -- Multi-Lingual Emotion Classification Using Convolutional Neural Networks -- On Parallel MLMC for Stationary Single Phase Flow Problem -- Numerical Parameter Estimates of Beta-uniform Mixture Models -- Large-Scale Computer Simulation of the Performance of the Generalized Nets Model of the LPF-algorithm -- Contributed Papers -- A New Error Estimate for a Primal-Dual Crank-Nicolson Mixed Finite Element Using Lowest Degree Raviart-Thomas Spaces for Parabolic Equations -- A Finite Volume Scheme for a Wave Equation with Several Time Independent Delays -- Recovering the Time-Dependent Volatility in Jump-Diffusion Models from Nonlocal Price Observations -- On the Solution of Contact Problems with Tresca Friction by the Semismooth* Newton Method -- Fitted Finite Volume Method for Unsaturated Flow Parabolic Problems with Space Degeneration -- Minimization of p-Laplacian via the Finite Element Method in MATLAB -- Quality Optimizationof Seismic-derived Surface Meshes of Geological Bodies. 330 $aThis book constitutes revised selected papers from the 13th International Conference on Large-Scale Scientific Computing, LSSC 23021, which was held in Sozopol, Bulgaria, during June 7-11, 2021. The 60 papers included in this book were carefully reviewed and selected from a total of 73 submissions. The volume also includes two invited talks in full paper length. The papers were organized in topical sections as follows: Fractional diffusion problems: numerical methods, algorithms and applications; large-scale models: numerical methods, parallel computations and applications; application of metaheuristics to large-scale problems; advanced discretizations and solvers for coupled systems of partial differential equations; optimal control of ODEs, PDEs and applications; tensor and matrix factorization for big-data analysis; machine learning and model order reduction for large scale predictive simulations; HPC and big data: algorithms and applications; and contributed papers. 410 0$aLecture Notes in Computer Science,$x1611-3349 ;$v13127 606 $aComputer science 606 $aComputer networks 606 $aData structures (Computer science) 606 $aInformation theory 606 $aNumerical analysis 606 $aComputer engineering 606 $aComputer science$xMathematics 606 $aTheory of Computation 606 $aComputer Communication Networks 606 $aData Structures and Information Theory 606 $aNumerical Analysis 606 $aComputer Engineering and Networks 606 $aMathematical Applications in Computer Science 615 0$aComputer science. 615 0$aComputer networks. 615 0$aData structures (Computer science) 615 0$aInformation theory. 615 0$aNumerical analysis. 615 0$aComputer engineering. 615 0$aComputer science$xMathematics. 615 14$aTheory of Computation. 615 24$aComputer Communication Networks. 615 24$aData Structures and Information Theory. 615 24$aNumerical Analysis. 615 24$aComputer Engineering and Networks. 615 24$aMathematical Applications in Computer Science. 676 $a502.85 676 $a004 702 $aLirkov$b Ivan$f1963- 702 $aMargenov$b Svetozar 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910552712003321 996 $aLarge-Scale Scientific Computing$9772719 997 $aUNINA