17th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2022)

Name: 17th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2022) | Salamanca, Spain, September 5-7, 2022, Proceedings
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Salamanca, Spain, September 5-7, 2022, Proceedings

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(Editor)

Springer (Publisher)

Published on 11. October 2022

XXI, 669 pages

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978-3-031-18050-7 (ISBN)

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Content

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 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
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 ? 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
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 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
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
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 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
2.2 Datasets
3 Methodology
3.1 Dataset Manipulation
3.2 YOLOX
4 Experimentation
5 Conclusion
References
Improving Malware Detection with a Novel Dataset Based on API Calls
1 Introduction
2 Related Work
3 Proposal
3.1 Format of the Samples
3.2 Used Datasets
3.3 Used ML Model
4 Results
5 Conclusion
References
Identifying Places Using Multimodal Social Network Data
1 Introduction
2 Related Work
3 Description of the System
4 Experimental Setup
4.1 Baselines
4.2 Combining Image and Text
4.3 Evaluation
5 Conclusions and Future Work
References
Monitoring Human Performance Through Deep Learning and Computer Vision in Industry 4.0
1 Introduction
2 Model Proposal
2.1 Manufacturing Description Language
2.2 Manufacturing Process Analyzer
2.3 Fatigue Analyzer
2.4 Recommendations Generator
3 Experimentation
4 Conclusions
References
Automatic Fish Size Estimation from Uncalibrated Fish Market Images Using Computer Vision and Deep Learning
1 Introduction
2 Fish Size Measuring Methodology
2.1 Inference of Input Data: Instance Segmentation and Classification
2.2 Ground Truth Size Estimation via Visual Metrology
2.3 Fish Size Regression
3 Experimental Evaluation
4 Results and Discussion
5 Conclusions
References
Vehicle Overtaking Hazard Detection over Onboard Cameras Using Deep Convolutional Networks
1 Introduction
2 Methodology
3 Experiments
3.1 Implementation Details
3.2 Data
3.3 Evaluation
3.4 Results
4 Conclusions
References
Image Classification Applied to the Problem of Conformity Check in Industry
1 Introduction
2 Related Work
3 Methodology and Results
3.1 Problem Statement - Verifying Presence by Classification
3.2 SVM with HoG
3.3 SVM with BoVW
3.4 Linear SVM with CNN Features
4 Conclusion
References
A Virtual Sensor Approach to Estimate the Stainless Steel Final Chemical Characterisation
1 Introduction
2 Materials and Methods
2.1 DataSet
2.2 Methods
3 Results
4 Conclusions
References
Convolutional Neural Networks for Structured Industrial Data
1 Introduction
2 Related Work
3 Materials and Methods
4 Contribution
4.1 Continuous Variable Transmission (CVT)
4.2 Secondary Metallurgy Process
5 Results and Discussion
6 Conclusions and Future Work
References
Classification of Polymers Based on the Degree of Their Transparency in SWIR Spectrum
1 Introduction
2 Problem Formulation
3 Method Statement
3.1 Polymer Types
3.2 SWIR Camera and Lights
3.3 Background
3.4 Object Detection Method
3.5 CNN for Image Transformation
4 Experiments Procedure
4.1 Hardware Conditions
4.2 Dataset Creation
4.3 ASP U-Net Training
5 Results
6 Conclusions
References
Deep Learning Based Baynat Foam Classification for Headliners Manufacturing
1 Introduction
2 Deep Learning Methods
2.1 Xception
2.2 Resnet50
2.3 MobilenetV2
2.4 InceptionV3
3 Experimental Results
4 Conclusions and Further Work
References
Special Session on Time Series Forecasting in Industrial and Environmental Applications
A GAN Approach for Anomaly Detection in Spacecraft Telemetries
1 Introduction
2 GANs and Anomaly Detection
3 Related Works
4 Data
5 Method
6 Results
7 Conclusion
References
Management and Forecasting of the Demand for Caskets in the Funeral Sector. Study Before and During the Covid-19 Pandemic
1 Introduction
2 The Funeral Services Industry
2.1 Funeral Services Sector in Data
3 Dataset Description
4 Methodology
5 Experiments and Results
5.1 Pre-covid 19 Model: Training Data Set 2016-2018 and Test Data Set 2019
5.2 Covid 19 Model: Training Data Set 2016-2018 and Test Data Set 2020
6 Conclusions and Future Work
References
Explainable Artificial Intelligence for the Electric Vehicle Load Demand Forecasting Problem
1 Introduction
2 Related Works
3 Methodology
3.1 Data Acquisition
3.2 Machine Learning Methods
3.3 Models Explainability
3.4 Quality Parameters
4 Results
4.1 Dataset Description
4.2 Results Discussion
4.3 Explainability
5 Conclusions
References
A Cluster-Based Deep Learning Model for Energy Consumption Forecasting in Ethiopia
1 Introduction
2 Related Works
3 Methodology
4 Analysis and Result Discussion
4.1 Data Description
4.2 Clustering Process
4.3 Results Achieved
5 Conclusions
References
Special Session on Optimization, Modeling and Control by Soft Computing Techniques
Abnormal Driving Behavior Identification Based on Naturalistic Driving Data Using LSTM Recurrent Neural Networks
1 Introduction
2 Vehicle Dynamics-Based Approach
3 Abnormal Behavior Identification by an LSTM NN Model
3.1 Selected Variables for the Classification Model
3.2 Deep LSTM Recurrent Neural Network Model for Classification
4 Results and Discussion
5 Conclusions and Future Works
References
Identification of Critical Subgraphs in Drone Airways Graphs by Graph Convolutional Networks
1 Introduction
2 Computational Approach
2.1 Semi-supervised Learning with Graph Convolutional Network
2.2 Enhanced GCN
2.3 Advanced GCN
3 Some Experimental Results
3.1 Basic GCN Dominance Results
3.2 Enhanced GCN Dominance Results
3.3 Advanced GCN Dominance Results
4 Conclusions and Future Work
References
Robust Velocity Control of an Automated Guided Vehicle Using Artificial Neural Networks
1 Introduction
2 Description of the System
2.1 AGV Model
3 Description of the Control Strategy
3.1 Neural Network Model
3.2 Reference Model
3.3 Neural Network Controller
4 Results
5 Conclusions and Future Works
References
Studying the Use of ANN to Estimate State-Space Variables for MIMO Systems in a NMPC Strategy
1 Introduction
2 MIMO System: Twin-Rotor
2.1 Mathematical Model Development
2.2 Study of Twin-Rotor Dynamics
3 Experiments and Results
3.1 ANN Model
3.2 NMPC Performance with ANN Model
4 Conclusions
References
Control of MIMO Systems with iMO-NMPC Strategy
1 Introduction
2 MIMO System Presentation
2.1 SISO System: SNL5
2.2 SISO System: SNL1
2.3 MIMO System: SNL5 and SNL1
3 NN Model
3.1 Topology Analysis
3.2 Prediction Analysis
4 iMO-NMPC Parameters (Control Strategy)
5 Results
5.1 Using Mathematical Model with iMO-NMPC
5.2 Using NN Model with the iMO-NMPC
5.3 Comparison of Prediction Models: Math. vs. NN
6 Conclusions
References
Optimization of Trajectory Generation for Automatic Guided Vehicles by Genetic Algorithms
1 Introduction
2 Environment Layout Model
3 Description of the Trajectory Optimization Process Based on Genetic Algorithms
3.1 Optimization Methodology
3.2 Genetic Algorithm
4 Results and Discussion
5 Conclusions and Future Works
References
Special Session on Soft Computing Applied to Renewable Energy Systems
Complementing Direct Speed Control with Neural Networks for Wind Turbine MPPT
1 Introduction
2 Mathematical Model of the Wind Turbine
2.1 DFIG Mathematical Description
3 MPPT Control Based on DSC and Neural Networks
4 Discussion of the Results
5 Conclusions and Future Works
References
A Control Approach on Hybrid Floating Offshore Wind Turbines for Platform and Generated Power Oscillations Reduction at Below-rated Wind Speed
1 Introduction
2 FOWT Model
3 Problem Statement
3.1 RAOs Evaluation
3.2 Control Statement
4 Results
5 Conclusions
References
Control Tuning by Genetic Algorithm of a Low Scale Model Wind Turbine
1 Introduction
2 Wind Turbine Modelling
2.1 Aerodynamic Model
3 Wind Turbine Low Scale Model
3.1 Blades and Pitch Mechanism
3.2 Electric Generator and Load Actuator
3.3 Measurement System
3.4 Microcontroller
3.5 Load Control System
3.6 Pitch Control System
3.7 Software Architecture
4 Experimental Results
5 Optimal Tuning by Genetic Algorithms
6 Conclusions
References
Pitch-Based Wind Turbine Tower Vibration Damping Optimized by Simulated Annealing
1 Introduction
2 Pitch-Based Wind Turbine Tower Vibration Damping
3 Tuning of the Controller by Simulated Annealing
3.1 Decision Variables
3.2 Constraints
3.3 Auxiliary Functions
3.4 Cost Function
3.5 Simulated Annealing Algorithm
4 Simulation Results and Discussion
5 Conclusions and Future Works
References
Neural Networks Techniques for Fault Detection and Offset Prediction on Wind Turbines Sensors
1 Introduction
2 Data Sets
3 Problem Statement
4 LSTM Architectures
5 Methodology
6 Experiments and Results
7 Conclusions and Future Work
References
Special Session on Pre-processing Big Data in Machine Learning
Errors of Identifiers in Anonymous Databases: Impact on Data Quality
1 Introduction
2 Data Collection
2.1 Data Enrichment
2.2 Errors of Identifiers
3 Data Quality
3.1 Quality Metrics
3.2 Aggregated Data Quality
4 Discussion
4.1 Data Cleaning
4.2 Impact of the Anonymization on the Data Quality
5 Conclusions
References
Feature-Aware Drop Layer (FADL): A Nonparametric Neural Network Layer for Feature Selection
1 Introduction
2 Related Works
3 Methodology
3.1 Description
3.2 Weight Initialization and Regularization
4 Experimentation
4.1 Datasets
4.2 Experimental Settings
4.3 Results and Discussion
5 Conclusions and Future Works
References
Classification Methods for MOBA Games
1 Introduction
2 Attribute Selection
3 The Proposed Methodology and Experimental Design
4 Results
5 Discussion and Further Research Line
References
Feature Ranking for Feature Sorting and Feature Selection, and Feature Sorting: FR4(FSoFS)FSo
1 Introduction
2 Feature Selection
3 The Proposed Methodology
4 Experimentation, Results and Discussion
5 Conclusions
References
Special Session on Tackling Real World Problems with Artificial Intelligence
Introducing Intelligence to the Semantic Analysis of Canadian Maritime Case Law: Case Based Reasoning Approach
1 Introduction
2 Problem Statement
3 Related Work
4 Machine Learning and Sentimental Analysis
5 Case-Based Reasoning Information Retrieval System (CBR-IR)
6 Conclusion
References
Case-Based Reasoning for the Prediction of Flash Flood
1 Introduction
2 Related Work
3 A CBR Proposal for the Flash-Flood Detection
3.1 The Representation of a Past Experience
3.2 The Three Rs CBR Process
3.3 Exploiting the CBR Tool
4 Experimentation and Discussion
5 Conclusion
References
Weakly Supervised Learning of the Motion Resistance of a Locomotive Powered by Liquefied Natural Gas
1 Introduction
2 Problem Statement
3 Proposed Method
3.1 Speed Model
3.2 Running Resistance Model
3.3 Slope Model
3.4 Numerical Optimization Problem
4 Numerical Results
5 Concluding Remarks and Future Work
References
Node Location Optimization for Localizing UAVs in Urban Scenarios
1 Introduction
2 Mathematical Model of the NLP
3 Genetic Algorithm Optimization
4 Results
5 Conclusions
References
Applying Deep Q-learning for Multi-agent Cooperative-Competitive Environments
1 Introduction
2 Cooperative-Competitive Multi-agent Environments
3 Single and Multi-agent Reinforcement Learning
4 Methods and Experiments
4.1 Proposed Approach
4.2 Experimental Setup
4.3 Discussion
5 Conclusions and Future Work
References
A Comparison of Two Speech Emotion Recognition Algorithms: Pepper Humanoid Versus Bag of Models
1 Introduction and Motivation
2 The SER Subsystems
2.1 Description of the Pepper and Its SER Subsystem
2.2 Descripcion of the SER-BOM Algorithm
3 Materials and Methods
3.1 SER Datasets
3.2 Design of the Testing Workbench
4 Numerical Results
4.1 Results for SER-Pepper
4.2 Results for SER-BoM
4.3 Comparison
5 Conclusion and Future Work
References
Fine-Tuning of Optimisation Parameters in a Firefly Algorithm in Inventory Management
1 Introduction
2 Related Work
3 Modelling the Inventory Management
4 Experimental Results and Discussion
4.1 Previous Research
4.2 Computational Results and Analysis
5 Conclusion and Future Work
References
Security Centric Scalable Architecture for Distributed Learning and Knowledge Preservation
1 Introduction
2 Related Work
3 Agricultural Use-Case for Distributed Learning
4 Functional and Non-Functional Requirements for the Distributed Learning Architecture
5 Distributed Learning System Architecture
5.1 Cloud Component Architecture
6 Architecture Validation
7 Discussions
8 Conclusions and Further Research
References
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17th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2022)

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