Applied Research in Fuzzy Technology de A.L. Ralescu

Applied Research in Fuzzy Technology: Three years of research at the Laboratory for International Fuzzy Engineering (LIFE), Yokohama, Japan: International Series in Intelligent Technologies, cartea 1

A.L. Ralescu

Fuzzy logic is `a recent revolutionary technology' which has brought together researchers from mathematics, engineering, computer science, cognitive and behavioral sciences, etc. The work in fuzzy technology at the Laboratory for International Fuzzy Engineering (LIFE) has been specifically applied to engineering problems. This book reflects the results of the work that has been undertaken at LIFE with chapters treating the following topical areas: Decision Support Systems, Intelligent Plant Operations Support, Fuzzy Modeling and Process Control, System Design, Image Understanding, Behavior Decisions for Mobile Robots, the Fuzzy Computer, and Fuzzy Neuro Systems. The book is a thorough analysis of research which has been implemented in the areas of fuzzy engineering technology. The analysis can be used to improve these specific applications or, perhaps more importantly, to investigate more sophisticated fuzzy control applications.

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Cuprins

1. Future Vision of Fuzzy Engineering.- 2. Decision Support System.- 2. 1 What is a decision support system ? - A case study of a foreign exchange dealing support expert system -.- 2. 2 Condition recognition in the decision support system.- 2. 3 Fuzzy evaluation and decision making in the decision support system.- 2. 4 Foreign exchange dealing supporting expert system - FOREX-.- 2.5 Prospects for the future.- References.- 3. Intelligent Plant Operation Support.- 3. 1 Functions desired for plant operation support.- 3. 2 Operation support system and background technologies.- 3. 3 Simulation by the simplified model.- 3. 4 Summary and prospects.- References.- 4. Fuzzy Modeling and Process Control System Design.- 4. 1 Subject for process control.- 4. 2 Fuzzy modeling of processes.- 4. 3 Control system design using a fuzzy model.- 4. 4 Application examples.- 4. 5 Epilogue.- References.- 5. Inference Function for Understanding Linguistic Instructions.- 5. 1 Linguistic fuzziness and inference.- 5. 2 Understanding linguistic instructions using rule based inference.- 5. 3 Understanding of linguistic instruction through case-based reasoning.- 5. 4 Cooperation of case-based reasoning and rule-based reasoning.- References.- 6. Fuzzy Theory in an Image Understanding Retrieval System.- 6. 1 Approach to image understanding in LIFE.- 6. 2 Recognition of face features based on a recognition model.- 6. 3 Facial image retrieval system.- 6. 4 Conclusion.- References.- 7. Research into Intelligent Behavior Decision Making of Robots.- 7. 1 Ambiguities in Intelligent Robots.- 7. 2 An Autonomous Mobile Robot System with Effective Decision Processes for Ambiguous States.- 7. 3 Macro Planning Section - Intelligent Path Planning Methods Based on Ambiguous Information -.- 7. 4 Macro Sensing Part -Hierarchical Sensor Fusion System for Living Object Recognition -.- 7. 5 Macro Behavior-Decision Part - Behavior and Decisions Fuzzy Algorithm Tunedaccording to the Control Purpose -.- 7. 6 Robot System for Actual Evaluation.- 7. 7 Conclusion.- References.- 8. Fuzzy Neural Net System.- 8. 1 What is Fuzzy Neural Net?.- 8.2 Fuzzy Associative Inference and Fuzzy Knowledge Recursive Learning.- 8. 3 Intellectual Interface through Fuzzy Neural net.- 8. 4 On-Line Learning using Fuzzy Neural Networks.- 8. 5 Future Development of Fuzzy Neural Networks.- References.- 9. Fuzzy Expert System Shell - LIFE FEShell -.- 9. 1 Introduction.- 9. 2 System Configuration.- 9. 3 Fuzzy Production System: FPS.- 9. 4 Fuzzy Frame System: FFS.- 9. 5 Object Editor. OE.- 9. 6 Summary and Problems to be Solved in the Future.- References.- 10. The Fuzzy Computer.- 10. 1 What is a fuzzy computer?.- 10. 2 The architecture of a fuzzy computer prototype system.- 10. 3 The fuzzy object-oriented language.- 10. 4 The fuzzy computer prototype system.- l0. 5 Conclusions.- References.