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Preface | ||
Pt. I | Fundamentals of Hybrid Systems | 1 |
Ch. 1 | Overview of Neural and Symbolic Systems | 3 |
Ch. 2 | Research in Hybrid Neural and Symbolic Systems | 21 |
Ch. 3 | Models for Integrating Systems | 35 |
Pt. II | Case Studies of Hybrid Neural Network and Expert Systems | 47 |
Ch. 4 | LAM Hybrid System for Window Glazing Design | 49 |
Ch. 5 | Hybrid Systems Approach to Nuclear Plant Monitoring | 77 |
Ch. 6 | Chemical Tank Control System | 109 |
Ch. 7 | Image Interpretation Via Fusion of Heterogeneous Sources Using a Hybrid Expert-Neural Network System | 121 |
Ch. 8 | Hybrid System for Multiple Target Recognition | 139 |
Pt. III | Analysis and Guidelines | 181 |
Ch. 9 | Guidelines for Developing Hybrid Systems | 183 |
Ch. 10 | Tools and Development Systems | 203 |
Ch. 11 | Summary and the Future of Hybrid Neural Network and Expert Systems | 215 |
References | 223 | |
Index | 239 |
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Add Hybrid Neural Network and Expert Systems, Hybrid Neural Network and Expert Systems presents the basics of expert systems and neural networks, and the important characteristics relevant to the integration of these two technologies. Through case studies of actual working systems, the author demonst, Hybrid Neural Network and Expert Systems to the inventory that you are selling on WonderClubX
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Add Hybrid Neural Network and Expert Systems, Hybrid Neural Network and Expert Systems presents the basics of expert systems and neural networks, and the important characteristics relevant to the integration of these two technologies. Through case studies of actual working systems, the author demonst, Hybrid Neural Network and Expert Systems to your collection on WonderClub |