Computational Intelligence Assisted Design In Industrial Revolution 4.0

Computational Intelligence Assisted Design framework mobilises computational resources, makes use of multiple Computational Intelligence (CI) algorithms and reduces computational costs. This book provides examples of real-world applications of technology. Case studies have been used to show the integration of services, cloud, big data technology and space missions. It focuses on computational modelling of biological and natural intelligent systems, encompassing swarm intelligence, fuzzy systems, artificial neutral networks, artificial immune systems and evolutionary computation. This book provides readers with wide-scale information on CI paradigms and algorithms, inviting readers to implement and problem solve real-world, complex problems within the CI development framework. This implementation framework will enable readers to tackle new problems without difficulty through a few tested MATLAB source codes

Introduction Introduction History of Computational Intelligence Need for Computational Intelligence in Design and Engineering Terms and Definitions Specialized and Application Areas Information Sources How to use this Book? HANDS-ON LEARNING OF COMPUTATIONAL INTELLIGENCE Global Optimization and Evolutionary Search Mimicking Natural Evolution Nondeterministic Methods for Optimisation and Machine Learning The Simple Genetic Algorithm Micro Genetic Algorithm Genetic Algorithm using Mendel’s Principles Characteristics of Evolutionary Design Tools Tutorials and Coursework Summary Artificial Neural Networks and Learning Systems Human Brain and Artificial Neural Networks ANN Design and Learning Learning Algorithms Tutorials and Coursework Fuzzy Logic and Fuzzy Systems Human Inference and Fuzzy Logic Fuzzy Logic and Decision Making Tutorial and Coursework CIAD AND ADVANCED COMPUTATIONAL INTELLIGENCE TOOLS CIAD - Computational Intelligence Aided Design Introduction Computational Intelligence Integrated Solver CIAD CIAE Intelligent Virtual Prototypes Physical Prototyping CIAM System Integration Cyber-physical Design Integration for Industry 4.0 Extra-Numerical Multi-objective Optimization Introduction History of Multi-objective Optimization Theory and Applications Multi-objective Genetic Algorithm Computational Swarm Intelligence Introduction Particle Swarm Optimization Ant Colony Optimization Swarm Fish Algorithm with Variable Population Swarm Bat Algorithm with Variable Population Firefly Algorithm with Variable Population Artificial Dolphin Swarm Algorithm Evolving Artificial Neural Networks in a Closed Loop Introduction Directly Evolving a Neural Network in a Closed-Loop Globally Optimized Design Through a Genetic Algorithm Neural Network Control for Linear and Nonlinear System Control Conclusions References Evolving Fuzzy Decision-Making Systems Introduction Formulation of a Fuzzy Decision-Making System Decision-Making Parameters Design Example for a Non-Linear System to Control Conclusion References Performance Assessment and Metric Indices Introduction Metric Indices Measure of Fitness of Fitting - Coefficients of Determination Measure of Error Heterogeneity - Relative Gini Index Measure of Trend - Trend Indices Fast Approach to Pareto-optimal Solution Recommendation Fitness Functions Test Functions CIAD FOR SCIENCE AND TECHNOLOGY Adaptive Bathtub-shaped Curve Introduction Parameterization Method via Radial Basis Functions Adaptive Bathtub-shaped Failure Rate Function Fitness Function Definition Simulations and Discussion Conclusions and Future Work Terahertz Spectroscopic Analysis Introduction THz-TDS Experimental Setup Sketch Statement of Mixture Component Determination Fitness Function Definition Uncertainty Studies Empirical Studies and Discussion Conclusions and Future Work Evolving a Sliding Robust Fuzzy System Introduction Application of Fuzzy Logic to Sliding Mode Control Fuzzy SMC System Designs Using a Conclusion References Space Tether for Payload Orbital Transfer Introduction Motorized Momentum Exchange Tether Payload Transfer Tether Strength Criterion Payload Transfer Objective Definition Simulations Conclusions and Future Work Structural Design for Heat Sinks Introduction Structural Modeling Experimental Setup Optimal Design Fitness Functions Empirical Results Conclusions and Future Work Battery Capacity Prediction Introduction Adaptive Bathtub-shaped Functions Battery Capacity Prediction Fitness Function Simulation Results and Discussion Conclusions and Future Work Parameter Determination for Fuel Cells Introduction Analytical Modeling Fitness Function Definition Empirical Results and Discussion Conclusions and Future Work CIAD Towards the Invention of a Microwave-Ignition Engine Introduction HCMI Design Evaluation and Virtual Prototyping Through Simulation Heuristic Methods and Improved GA Search Case Studies Virtual Prototyping Results and Comparison Conclusion References Control for Semi-Active Vehicle Suspension System Introduction Two-Degree-of-Freedom Semi-active Suspension System Sliding Mode Control with Skyhook Surface Scheme Fuzzy Logic Control Fuzzy Sliding Mode Control with Switching Factor - F SMC Polynomial Function Supervising F SMC - An Improvement Road Surface Profile - the Modeling of the Source of Uncertainty Uncertainty Studies Simulations Conclusions and Future Work CIAD FOR SOCIAL SCIENCES Exchange Rate Modeling and Decision Support Introduction Exchange Rate Determination Model Fitness Function of Regression Modeling Empirical Results and Discussion Conclusions and Future Work Quantitative Modeling of Electricity Consumption Introduction Quantitative modeling of national electricity consumption Definition of Fitness Function Numerical Results Social, Economic and Environmental Impacts Conclusions and Future Work CIAD Gaming Support for Electricity Trading Decisions Introduction Modelling Intelligent Market Behaviors Intelligent Agents and Modelling Model Analysis and Verification Applications of the Model Conclusions References Dynamic Behavior of Rural Regions with CO2 Emission Estimation Introduction CO2 Emission Estimation of Productive Activity Hybrid Modeling of the Functional Region Fitness Function Definition Empirical Results and Discussion Conclusions and Future Work Spatial Analysis of Functional Region of Suburban-Rural Areas Introduction Spatial Modeling of the Functional Regions Sensitive Analysis to Functional Distance Fitness Function Empirical Results and Discussion Conclusions and Future Work CIAD for Industry 4.0 Predictive Customization Introduction Customization in Industry 4.0 Methodology and CIAD Approaches Case Study Discussion and Conclusion References Glossary

Dr. Yi Chen is a lecturer in Dynamics and Control at the School of Engineering and Built Environment at Glasgow Caledonian University.