Ulteriori informazioni
Informationen zum Autor SEPPO J. OVASKA , DSc (Tech), is a professor in the Department of Electrical and Communications Engineering at Helsinki University of Technology, Finland. He is a senior member of the IEEE, and has published more than 180 papers in peer-reviewed journals and international conferences. Klappentext This uniquely crafted work combines the experience of many internationally recognized experts in the soft- and hard-computing research worlds to present practicing engineers with the broadest possible array of methodologies for developing innovative and competitive solutions to real-world problems. Each of the chapters illustrates the wide-ranging applicability of the fusion concept in such critical areas as* Computer security and data mining* Electrical power systems and large-scale plants* Motor drives and tool wear monitoring* User interfaces and the World Wide Web* Aerospace and robust controlThis must-have guide for practicing engineers, researchers, and R&D managers who wish to create or understand computationally intelligent hybrid systems is also an excellent primary source for graduate courses in soft computing, engineering applications of artificial intelligence, and related topics. Zusammenfassung Soft computing is an emerging collection of methodologies that exploit tolerances for imprecision, uncertainty, and partial truth to achieve robustness, tractability, and low total cost. Hard computing solutions are usually more straightforward to analyze, and feature more predictable behavior and stability. Inhaltsverzeichnis Contributors xv Foreword xvii David B. Fogel Preface xix Editor's Introduction to Chapter 1 1 1 Introduction to Fusion of Soft Computing and Hard Computing 5 Seppo J. Ovaska 1.1 Introduction 5 1.1.1 Soft Computing 5a 1.1.2 Fusion of Soft-Computing and Hard-Computing Methodologies 7 1.2 Structural Categories 9 1.2.1 Soft Computing and Hard Computing Are Isolated from Each Other 10 1.2.2 Soft Computing and Hard Computing Are Connected in Parallel 11 1.2.3 Soft Computing with Hard-Computing Feedback and Hard Computing with Soft-Computing Feedback 12 1.2.4 Soft Computing is Cascaded with Hard Computing or Hard Computing is Cascaded with Soft Computing 12 1.2.5 Soft-Computing-Designed Hard Computing and Hard-Computing-Designed Soft Computing 13 1.2.6 Hard-Computing-Augmented Soft Computing and Soft-Computing-Augmented Hard Computing 14 1.2.7 Hard-Computing-Assisted Soft Computing and Soft-Computing-Assisted Hard Computing 15 1.2.8 Supplementary Categories 16 1.2.9 General Soft-Computing and Hard-Computing Mapping Functions 19 1.3 Characteristic Features 19 1.3.1 Proportional Integral Derivative Controllers 20 1.3.2 Physical Models 20 1.3.3 Optimization Utilizing Local Information 21 1.3.4 General Parameter Adaptation Algorithm 22 1.3.5 Stochastic System Simulators 22 1.3.6 Discussion and Extended Fusion Schemes 22 1.4 Characterization of Hybrid Applications 24 1.5 Conclusions and Discussion 25 References 27 Editor's Introduction to Chapter 2 31 2 General Model for Large-Scale Plant Application 35 Akimoto Kamiya 2.1 Introduction 35 2.2 Control System Architecture 36 2.3 Forecasting of Market Demand 37 2.4 Scheduling of Processes 39 2.4.1 Problem Decomposition 39 2.4.2 Hybrid Genetic Algorithms 42 2.4.3 Multiobjective Optimization 43 2.5 Supervisory Control 45 2.6 Local Control 47 2.7 General Fusion Model and Fusion Categories 49 2.8 Conclusions 51 References 51 Editor's Introduction to Chapter 3 57 3 Adaptive Flight Control: Soft Computing with Hard Constraints ...
