**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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**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 - FSMC

Polynomial Function Supervising FSMC - 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 *CO*2
Emission Estimation

Introduction

*CO*2 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