Preface
Organization
Contents – Part I
Contents – Part II
Neural Network (NN) Theory, NN-Based Control Systems, Neuro-System Integration and Engineering Applications
ESN-Based Control of Bending Pneumatic Muscle with Asymmetric and Rate-Dependent Hysteresis
1 Introduction
2 The FSBPM
2.1 Structure of the FSBPM
2.2 The Asymmetric Rate-Dependent Hysteresis of the FSBPM
2.3 Mathematical Description of the FSBPM
3 Feedback Control Strategy Combined with the Feedforward Compensation
3.1 Inversion of the Hysteresis Based on ESN
3.2 Feedback Control Strategy Based on Feedforward Compensation
4 Experiments
4.1 Experimental Platform
4.2 Feedback Control Experiments
5 Conclusions
References
Image Reconstruction and Recognition of Optical Flow Based on Local Feature Extraction Mechanism of Visual Cortex
1 Introduction
2 Methods
2.1 MT Optical Flow Stimulation
2.2 Image Reconstruction Using NMF Algorithm
2.3 Image Reconstruction Using the SNN Model
3 Results
4 Conclusion
4.1 Summary
4.2 Outlook
References
Conditional Diffusion Model-Based Data Augmentation for Alzheimer's Prediction
1 Introduction
2 Method
2.1 Overview
2.2 Diffusion Probabilistic Model
2.3 Conditional DDPM
3 Experiments
3.1 Dataset and Experiment Design
3.2 Evaluation of Generated Data
3.3 Evaluation with Compared Methods
4 Conclusion
References
Design of Dissolved Oxygen Online Controller Based on Adaptive Dynamic Programming Theory
1 Introduction
2 Preliminary Knowledge
2.1 Optimal Problem Formulation
2.2 Online ESN-ADP Algorithm
2.3 FRRLS Algorithm for Training ESN-ADP
3 Convergence of ESN-Based Value Function Approximation
3.1 Convergence of ESN-Based Value Function Approximation
4 Experiment and Discussion
5 Conclusion
References
Ascent Guidance for Airbreathing Hypersonic Vehicle Based on Deep Neural Network and Pseudo-spectral Method
1 Introduction
2 Dynamic Modeling
3 Guidance Law Design
3.1 Offline Trajectory Database Establishment
3.2 DNN Structure and Training
3.3 The Sequential Calling Strategy and the Overall Scheme
4 Numerical Simulations
4.1 The Database Establishment
4.2 Real-Time Performance
4.3 Comparison of Different Numbers of the DNNs
5 Conclusion
References
Machine Learning and Deep Learning for Data Mining and Data-Driven Applications
Image Intelligence-Assisted Time-Series Analysis Method for Identifying “Dispersed, Disordered, and Polluting” Sites Based on Power Consumption Data
1 Introduction
2 Preliminary
2.1 Clustering Algorithm
2.2 Gramian Angular Field
3 Algorithm Procedure
3.1 H-K-means
3.2 Imaging Time Series
3.3 Mutual Information
3.4 Perceptual Hash Algorithm
4 Practical Validation
4.1 Background
4.2 Implementation
4.3 Results
5 Conclusion
References
Non-intrusive Load Identification Based on Steady-State V-I Trajectory
1 Introduction
2 Construction of V-I Trajectory Pixelization
3 Construction and Optimization of Convolutional Neural Networks
3.1 Construction of Neural Networks
3.2 Bayesian Optimization Algorithm
4 Experiment and Result Analysis
4.1 Datasets and Evaluation Criteria
4.2 Case Analysis
5 Summary
References
Prediction of TP in Effluent at Multiple Scales Based on ESN
1 Introduction
2 Preliminary
2.1 Multiscale Time Series
2.2 Echo State Network
3 Proposed Methodology
3.1 Data Weighted Average Processing
3.2 Prediction Method Based on WAP
4 Simulation
5 Conclusion
References
Application of WOA-SVM Based Algorithm in Tumor Cell Detection Research
1 Introduction
2 Methodology
2.1 Support Vector Machine
2.2 Whale Optimization Algorithm
3 WOA-SVM Algorithm Model
3.1 WOA-SVM Algorithm Model Construction
3.2 Evaluation Criteria for the WOA-SVM Algorithm
4 Analysis of Arithmetic Cases Based on the WOA-SVM Algorithm
4.1 Data set Analysis
4.2 Analysis of the Findings from Experiments
5 Conclusion
References
MM-VTON: A Multi-stage Virtual Try-on Method Using Multiple Image Features
1 Introduction
2 Related Work
2.1 Virtual Try-on
2.2 Image Synthesis
2.3 Features of Our Work
3 MM-VTON
3.1 Overview of MM-VTON
3.2 Clothes Warping Module (CWM)
3.3 Semantic Prediction Module (SPM)
3.4 Generative Module (GM)
4 Experiments
4.1 Experimental Setup
4.2 Quantitative Results
4.3 Qualitative Results
5 Conclusion
References
Self-Attention-Based Reconstruction for Planetary Magnetic Field
1 Introduction
2 SAITS Model Introduction
2.1 Joint-Optimization Training Approach
2.2 SAITS Model
3 Experiments
3.1 Description of Experimental Data
3.2 Reconstruction Results
4 Conclusion and Future Work
References
Semi-supervised Multi-class Classification Methods Based on Laplacian Vector Projection-1pc
1 Introduction
2 Semi-supervised Multi-class LapPVPs
2.1 OVO-LapPVP
2.2 OVR-LapPVP
2.3 Comparison of Multi-class LapPVP
3 Experiments
3.1 Experimental Setup
3.2 Results and Discussion
4 Conclusion
References
Integrating EMD, LMD and TCN Methods for COVID-19 Forecasting
1 Introduction
2 Related Works
2.1 Empirical Mode Decomposition (EMD)
2.2 Local Mean Decomposition (LMD)
2.3 Temporal Convolutional Network (TCN)
3 Problem Formulation
4 Methodology
4.1 Time Series Decomposition
4.2 Proposed EMD-LMD-TCN Model
5 Experiment Setup
5.1 Data Description
5.2 IMF and PF Components Extraction
5.3 Training Details
6 Experiment Results
6.1 Evaluation Metrics
6.2 Forecasting Performance
7 Conclusion
References
Computational Intelligence, Nature-Inspired Optimizers, and Their Engineering Applications
LOS Guidance Law for Unmanned Surface Vehicle Path Following with Unknown Time-Varying Sideslip Compensation-1pc
1 Introduction
2 Problem Formulation
3 SLOS Guidance Design and Analysis
3.1 Sideslip Angle Identification
3.2 Guidance Law Design
4 Stability Analysis
5 Simulation Experiments
6 Conclusions
References
Application of Bat Algorithm to Reduce Power Loss in Electrical Power Systems
1 Introduction
2 Problem Formulation
2.1 Equality Constraints
2.2 Inequality Constraints
2.3 Handling of Constraints
3 Bat Algorithm
3.1 The Pseudo Code of BA
3.2 Implementation of BA to Reactive Power Dispatch
4 Result and Discussion
5 IEEE 39 Bus System
5.1 IEEE 57 Bus System
6 Conclusion and Future Work
References
An Enhanced Subregion Dominance Relation for Evolutionary Many-Objective Optimization
1 Introduction
2 Related Work
3 Proposed Approach
3.1 Population Association and Subregion
3.2 Enhancing Convergence and Diversity
3.3 ESD-Dominance Relation
3.4 Framework of ESD-NSGA-II
4 Experimental Study
4.1 Benchmark Problems and Parameter Settings
4.2 Performance Metrics
4.3 Comparison Results
4.4 Effect the Neighborhood Size
5 Conclusion
References
A Stacked Autoencoder Based Meta-Learning Model for Global Optimization
1 Introduction
2 Related Work
2.1 Algorithm Selection
2.2 Stacked Autoencoder
3 Adaptive Data-Driven Recommendation Model
3.1 Extracting Module
3.2 Training Module
3.3 Recommending Module
4 Experiment Validation
4.1 Experiment Setup
4.2 Experiment Result
5 Conclusion
References
Optimization Design of Photovoltaic Power Generation System Under Complex Lighting Conditions
1 Introduction
2 Photovoltaic Cell Modeling and Analysis
2.1 Mathematical Model of Photovoltaic Cell
2.2 Selection of Photovoltaic Cells
2.3 Output Characteristics of Photovoltaic Cells
3 Simulation of Photovoltaic Array Modeling Under Complex Light Intensity
3.1 Simulation Analysis of Output Curve of S-configuration Photovoltaic Array
3.2 Mathematical Model of TCT Photovoltaic Configuration
3.3 Simulation Analysis of TCT Configuration Photovoltaic Array Output Curve
4 Application of Micro Inverters in Solving Photovoltaic Arrays Under Complex Light Conditions
5 Configuration Scheme of Photovoltaic Array
5.1 Uniform Light Receiving Area
5.2 Unevenly Illuminated Areas
6 Conclusion
References
Analysis of the Impact of Regional Customer Charging on the Grid Under the Aggregator Model
1 First Section
2 Operation Model
2.1 Participant
2.2 Form of Cooperation
3 User Travel Characteristics and User Dispatchable Potential Indicators in the Region
3.1 User Travel Characteristics in the Region
3.2 User Dispatchable Potential Indicators
4 Optimal Scheduling Model for Aggregator Collaborative Users
4.1 Objective Function
4.2 Constraints
5 Example Analysis
6 Conclusion
References
Indicators Directed Multi-strategy Artificial Bee Colony Algorithm
1 Introduction
2 Artificial Bee Colony Algorithm
3 Proposed Approach
3.1 Multiple Search Strategies
3.2 Evaluation Indicators
3.3 Framework of Proposed Approach
4 Experimental Study
4.1 Test Problems and Variables Settings
4.2 Parameter Analysis of L
4.3 Tests on the Benchmark Issues
5 Conclusion
References
Energy-Efficient Cellular Offloading Optimization for UAV-Aided Networks
1 Introduction
2 System Model
2.1 Signal Model
2.2 Computation Model
2.3 Problem Formulation
3 Framework Design
3.1 Optimization of K-Means Clustering Algorithm
3.2 Power Allocation Based on DDPG Algorithm
4 Numerical Results and Analysis
4.1 Simulation Setup
4.2 Results and Discussions
5 Conclusion
References
Artificial Bee Colony Based on Adaptive Search Strategies and Elite Selection Mechanism-1pc
1 Introduction
2 Artificial Bee Colony Algorithm
3 Proposed Approach
3.1 Tolerance-Based Strategy Selection Method
3.2 Elite Selection for the Onlooker Bee Phase
3.3 Framework of Proposed Approach
4 Experimental Study
4.1 Benchmark Problems and Parameter Settings
4.2 Study on the Parameter M
4.3 Comparison of ASESABC with Other ABC Algorithms
5 Conclusion
References
Minimization of Active Power Loss Using Enhanced Particle Swarm Optimization
1 Introduction
2 Problem Formulation
2.1 Formulation of Voltage Stability Indices
2.2 Steps Involve in Identifying Critical Node in EPS
2.3 Formulation of RPO
3 Particle Swarm Optimization (PSO)
3.1 PSO and It is Variants
3.2 EPSO
4 Result and Discussion
4.1 Voltage Stability Indices
4.2 Reactive Power Optimization
5 Conclusion and Future Work
References
Preference Weight Vector Adjustment Strategy Based Dynamic Multiobjective Optimization
1 Introduction
2 Background
3 Proposed Algorithm
3.1 MOEA/D
3.2 Reference Vector Adjustment Strategy
3.3 Dynamic Response Strategy
4 Simulation and Evaluation
4.1 Performance Indicators
4.2 Compared Algorithms
4.3 Parameter Settings
4.4 Comparative Study
5 Conclusion
References
Complementary Environmental Selection for Evolutionary Many-Objective Optimization
1 Introduction
2 Background
2.1 Problem Descriptions
2.2 Environmental Selection
3 Proposed Approach
3.1 Basic Framework
3.2 Complementary Environmental Selection
4 Experimental Study
4.1 Benchmark Problems and Parameter Settings
4.2 Results and Discussions
5 Conclusion
References
An Investigation on the Effects of Exemplars Selection on Convergence and Diversity in Large-Scale Particle Swarm Optimizer
1 Introduction
2 Related Work
2.1 Coupled Control over Convergence and Diversity
2.2 Decoupled Control over Convergence and Diversity
3 Design Guideline
3.1 Selection Model of Candidate Exemplars
3.2 Number of Candidate Exemplars
3.3 Update Strategy
4 Experiment Study
4.1 Experimental Results of Convergence
4.2 Experimental Results of Diversity
4.3 Summary and Analysis
5 Conclusions and Future Work
Appendix
References
A LSTM Assisted Prediction Strategy for Evolutionary Dynamic Multiobjective Optimization
1 Introduction
2 Related Work
2.1 Prediction Based DMOEAs
2.2 Long Short-Term Memory
3 LSTM Assisted Prediction Strategy Based DMOEA
3.1 The Framework of LP-DMOEA
3.2 LSTM Assisted Prediction Strategy
4 Experiment
4.1 The Framework of LP-DMOEA
4.2 Analysis of Parameter K
4.3 Comparisons with Various DMOEAs
4.4 Running Time of Various DMOEAs
5 Conclusion
References
An Adaptive Brain Storm Optimization Based on Hierarchical Learning for Community Detection
1 Introduction
2 Background Knowledge
2.1 Modularity
2.2 Normalized Mutual Information
3 Proposed Algorithms
3.1 Framework of ABSO-HL
3.2 Initialization and Representation
3.3 K-means Clustering
3.4 Mutation and Crossover
3.5 Hierarchical Learning
4 Experiments
4.1 Experimental Settings
4.2 Experimental Results and Analysis
5 Conclusions
References
Optimization Method of Multi-body Integrated Energy System Considering Air Compression Energy Storage
1 First Section
2 Framework for IES in Industrial Parks
3 Mathematical Models
3.1 Equipment Model
3.2 ESP Model
4 Two-Tier Game Model
4.1 Objective Function
4.2 Constraints
5 Analysis of Results
6 Conclusion
References
Sequential Seeding Initialization for SNIC Superpixels
1 Introduction
2 Preliminaries
2.1 Grid Sampling Initialization
2.2 Non-Iterative Clustering
3 Methodology
3.1 Sequential Sampling
3.2 Linear Path Correlation
4 Experiments
4.1 Metrical Evaluation
4.2 Visual Comparison
5 Conclusion
References
Dynamic Multi-objective Prediction Strategy for Transfer Learning Based on Imbalanced Data Classification
1 Introduction
2 Preliminary
2.1 Transfer Component Analysis
3 Proposed Methodology
3.1 Knee Points
3.2 Data Augmentation Strategy Based on ELM-SMOTE
3.3 The Process of ICTr-MOEA/D
4 Experiments
4.1 Performance Indicators
4.2 Compare Algorithms
4.3 Performance on DF Problems
5 Conclusion
References
A Twin Learning Evolutionary Algorithm for Capacitated Vehicle Routing Problem
1 Introduction
2 Preliminaries
2.1 CVRP
2.2 Meta-Heuristic Algorithms for CVRP
2.3 Learning Based Algorithms for CVRP
3 Twin Learning Framework
3.1 Twin Task Matching
3.2 Twin Task Construction
3.3 Mapping Strategy
4 Twin Learning Evolutionary Algorithm for CVRP
4.1 Match the Twin CVRP for Target CVRP
4.2 Construct Feasible Solutions for CVRP
5 Experiment on CVRP Benchmarks
5.1 Experimental Configuration
5.2 Results and Discussion
6 Conclusion
References
Research on Full-Coverage Path Planning Method of Steel Rolling Shop Cleaning Robot
1 Introduction
2 Brief Description of the Algorithm Principle
2.1 Map Environment Modeling
2.2 Breadth-First Search Algorithm
2.3 A Algorithm
3 Improved Algorithm for Full Coverage Path Planning in Clean Areas
3.1 Improved A* Obstacle Avoidance Path Planning
3.2 Improved Round-Trip Full-Coverage Path Planning Algorithm
4 Simulation and Data Analysis
5 Conclusion
References
Deep Reinforcement Learning Method of Target Hunting for Multi-agents with Flocking Property
1 Introduction
2 Reinforcement Learning Process
3 Multi-agents Learning Algorithm
4 Reward Function of Hunting Target
4.1 Reward Function of Danger Zone Model
4.2 Establishment of Flocking Reward Function
5 Simulation Results and Analysis
6 Conclusion
References
Design of Particle Swarm Optimized Fuzzy PID Controller and Its Application in Superheat Degree Control
1 Introduction
2 Description of the Controlled Object
2.1 Description of Experimental Setup and Superheat
2.2 Control System Structure
3 Implementation of the Control Algorithm
3.1 Implementation of Fuzzy PID Algorithm
3.2 Determination of Quantifiers and Theoretical Domains
3.3 System Model Identification
4 Design of Particle Swarm Optimized Fuzzy PID Controller
4.1 Introduction of Pso Optimization Algorithm
4.2 Optimization Results
5 Control Effect Verification
5.1 Simulation Verification
5.2 Experimental Validation
5.3 System Analysis
6 Conclusion
References
A Multi-style Interior Floor Plan Design Approach Based on Generative Adversarial Networks
1 Introduction
2 Datasets and Evaluation Metrics
2.1 Datasets Pre-processing
2.2 Evaluation and Metrics
3 Overall Design Framework
3.1 Pix2pix and Pix2pixHD
3.2 Dual-Module Structure
4 Experiment
4.1 Algorithm Comparison and Selection
4.2 The Experimental Comparison of Single-Module and Dual-Module Approach
4.3 Multi-style Interior Floor Plan Design
5 Conclusions
References
Linear Model-Based Optimal VVC Intercoding Rate Control Scheme
1 Introduction
2 Proposed Linear R-QP Model
3 Proposed RC Scheme
3.1 Optimized Solution
4 Experimental Results
4.1 Performance Evaluations
4.2 Bitrate Accuracy
5 Conclusions
References
Detection and Analysis of Hanging Basket Wire Rope Broken Strands Based on Mallat Algorithm
1 Introduction
2 Magnetic Field Distribution Detection
3 Wire Rope Defect Detection Design
3.1 Wire Rope Modeling
3.2 Excitation Device
3.3 Leakage Field Simulation
3.4 Signal Acquisition Module
3.5 Signal Processing Module
4 Wire Rope Defect Signal Processing
4.1 Mallat Algorithm
4.2 Machine Learning Based Wire Rope Defect Detection
5 Experimental Validation
6 Conclusion
References
PointAF: A Novel Semantic Segmentation Network for Point Cloud
1 Introduction
2 Related Work
2.1 DL in Point Cloud
2.2 Attention Mechanism
2.3 Point Cloud Segmentation
3 Method
3.1 AF Module
3.2 FM Module
4 Experiment
4.1 Evaluation Criteria
4.2 3D Segmentation
5 Conclusion
References
Accurate Detection of the Workers and Machinery in Construction Sites Considering the Occlusions
1 Introduction
2 Methodology
2.1 Data Augmentation
2.2 YOLOv7
2.3 Improved IoU Loss Function
3 Experimental Results and Discussion
3.1 Metric Evaluation
3.2 Data Preparation
3.3 Experimental Setting
3.4 Experimental Results and Analysis
4 Conclusion
References
Research on Crack Identification of Highway Asphalt Pavement Based on Deep Learning
1 Foreword
2 Data Collection and Processing
3 Retinex Image Enhancement
4 Implementation of Yolov5 Algorithm
4.1 Yolov5 Network Architecture
4.2 Improvement and Evaluation Index of Yolov5 Algorithm
5 Experimental Results and Analysis
6 Conclusion
References
Author Index