Description
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
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?
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 - FSMC
Polynomial Function Supervising FSMC - 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
