Computational Intelligence Assisted Design: In Industrial Revolution 4.0

Yi Chen
Industry 4.0 Artificial Intelligence Laboratory
Dongguan University of Technology
Songshanhu, Dongguan 523808, China

Yun Li
Professor in Design, Manufacture and Engineering Management
Faculty of Engineering, University of Strathclyde
Glasgow G1 1XJ, UK

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Table of Contents

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?

 

Part I. 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

 

Part II. 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

 

Part III. 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

 

Part IV. 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