Hybrid Architectures for Intelligent SystemsCRC Press, 1992. gada 21. febr. - 448 lappuses Hybrid architecture for intelligent systems is a new field of artificial intelligence concerned with the development of the next generation of intelligent systems. This volume is the first book to delineate current research interests in hybrid architectures for intelligent systems. The book is divided into two parts. The first part is devoted to the theory, methodologies, and algorithms of intelligent hybrid systems. The second part examines current applications of intelligent hybrid systems in areas such as data analysis, pattern classification and recognition, intelligent robot control, medical diagnosis, architecture, wastewater treatment, and flexible manufacturing systems. Hybrid Architectures for Intelligent Systems is an important reference for computer scientists and electrical engineers involved with artificial intelligence, neural networks, parallel processing, robotics, and systems architecture. |
No grāmatas satura
1.–5. rezultāts no 79.
. lappuse
... Hybrid Systems , 167 Summary , 170 References , 170 Chapter 9 FUZZY HYBRID SYSTEMS C. Posey , A. Kandel , and G. Langholz Introduction , 174 Expert Systems , 175 Neural Networks , 176 Fuzzy Hybrid Systems , 179 Conversion from Fuzzy ...
... Hybrid Systems , 167 Summary , 170 References , 170 Chapter 9 FUZZY HYBRID SYSTEMS C. Posey , A. Kandel , and G. Langholz Introduction , 174 Expert Systems , 175 Neural Networks , 176 Fuzzy Hybrid Systems , 179 Conversion from Fuzzy ...
. lappuse
... HYBRID DISTRIBUTED / LOCAL CONNECTIONIST ARCHITECTURES T. Samad Introduction , 200 Distributed and Local Representations , 201 Hybrid Distributed / Local Networks , 202 A Connectionist Rule - Based System , 205 A Knowledge Base Browser ...
... HYBRID DISTRIBUTED / LOCAL CONNECTIONIST ARCHITECTURES T. Samad Introduction , 200 Distributed and Local Representations , 201 Hybrid Distributed / Local Networks , 202 A Connectionist Rule - Based System , 205 A Knowledge Base Browser ...
. lappuse
... HYBRID EXPERT SYSTEM D. L. Hudson , M. E. Cohen , P. W. Banda , and M. S. Blois 329 Introduction , 330 Application , 331 Model for Prognostic Factors , 332 Chromatographic Analysis , 337 Conclusion , 340 References , 341 Chapter 16 ...
... HYBRID EXPERT SYSTEM D. L. Hudson , M. E. Cohen , P. W. Banda , and M. S. Blois 329 Introduction , 330 Application , 331 Model for Prognostic Factors , 332 Chromatographic Analysis , 337 Conclusion , 340 References , 341 Chapter 16 ...
. lappuse
... HYBRID NEURAL AND SYMBOLIC PROCESSING APPROACH TO FLEXIBLE MANUFACTURING SYSTEMS SCHEDULING L. C. Rabelo Introduction , 380 Hybrid Neural and Symbolic Processing Systems , 382 Intelligent FMS Scheduling ( IFMSS ) Framework , 383 ...
... HYBRID NEURAL AND SYMBOLIC PROCESSING APPROACH TO FLEXIBLE MANUFACTURING SYSTEMS SCHEDULING L. C. Rabelo Introduction , 380 Hybrid Neural and Symbolic Processing Systems , 382 Intelligent FMS Scheduling ( IFMSS ) Framework , 383 ...
11. lappuse
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Saturs
NEURAL NETS AND FUZZY LOGIC | 3 |
Basic Components of Modular Neural Networks | 12 |
Modular Networks | 19 |
NODE ERROR ASSIGNMENT IN EXPERT NETWORKS | 29 |
PERFORMANCE ISSUES OF A HYBRID SYMBOLIC | 46 |
LEARNING SYSTEM FOR GRAMMARS AND LEXICONS | 49 |
INTEGRATION OF NEURAL NETWORK TECHNIQUES WITH | 71 |
A PARALLEL DISTRIBUTED APPROACH FOR KNOWLEDGE | 87 |
Data Classification and Pattern Recognition | 286 |
Conclusions | 297 |
GoalDirected Training of Neural Networks | 306 |
Application of Robotic Skill Acquisition to Aircraft | 315 |
Conclusions | 324 |
71 | 326 |
Introduction | 330 |
Chromatographic Analysis | 337 |
A HYBRID ARCHITECTURE FOR FUZZY | 135 |
MODELS AND GUIDELINES FOR INTEGRATING EXPERT | 153 |
49 | 170 |
FUZZY HYBRID SYSTEMS C Posey A Kandel | 174 |
HYBRID DISTRIBUTEDLOCAL CONNECTIONIST | 199 |
HIERARCHICAL STRUCTURES IN HYBRID SYSTEMS | 221 |
RULE COMBINING A NEURAL NETWORK APPROACH | 255 |
A PROBLEM SOLVING SYSTEM FOR DATA ANALYSIS | 279 |
135 | 341 |
REPRESENTING EXPERT KNOWLEDGE IN NEURAL | 345 |
AN INTELLIGENT HYBRID SYSTEM FOR WASTEWATER | 357 |
A HYBRID NEURAL AND SYMBOLIC PROCESSING | 379 |
221 | 386 |
AUTHORS BIOGRAPHICAL INFORMATION | 407 |
Citi izdevumi - Skatīt visu
Hybrid Architectures for Intelligent Systems Abraham Kandel,Gideon Langholz Ierobežota priekšskatīšana - 2020 |
Hybrid Architectures for Intelligent Systems Abraham Kandel,Gideon Langholz Ierobežota priekšskatīšana - 2020 |
Hybrid Architectures for Intelligent Systems Abraham Kandel,Gideon Langholz Priekšskatījums nav pieejams - 1992 |
Bieži izmantoti vārdi un frāzes
activation airspeed analysis antecedent applications approximate reasoning architecture Artificial Intelligence artificial neural networks assigned associated backpropagation clause collector cells combined complex components concept connectionist expert systems connections decision tree defined distributed representations error evaluated example factors Figure function fuzzy logic Fuzzy Sets glideslope goal grammar heuristic hidden nodes hierarchical hybrid systems IEEE implemented inference engine initial input layer integration knowledge acquisition knowledge base knowledge representation knowledge rules knowledge-based systems learning algorithm learning system linear LSGL Machine methods microfeatures modified negation neural computing neural net neural network approach neurons operator optimal pattern recognition performance phase premise problem solving procedure programming represent RSA2 rule-based system scheduling scheme selection semantic network simulation solution specific strategies structure symbolic systems and neural task techniques threshold Throttle unit University variables vector weights