Elsevier S & T

Knowledge-Based Systems, Four-Volume Set: Techniques and Applications

Leondes, Cornelius T.

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Table of contents

Cover
CONTENTSv
CONTRIBUTORSxix
PREFACExxv
Chapter 1. Active Knowledge-Based Systems1
I. Introduction1
II. Active Database and Knowledge Base Systems3
III. Device: An Active Object-Oriented Knowledge Base System13
IV. Applications of Active Knowledge Base Systems20
V. Conclusions and Future Directions33
Appendix33
References34
Chapter 2. Knowledge Development Expert Systems and Their Application in Nutrition37
I. Introduction38
II. Knowledge-Based Tutoring Systems38
III. Nutri-Expert, an Educational System in Nutrition40
IV. Heuristic Search Algorithms to Balance Meals50
V. Concluding Discussion64
References64
Chapter 3. Geometric Knowledge-Based Systems Framework for Structural Image Analysis and Postprocess67
I. Introduction68
II. Structural Representation of Images69
III. Previous Work in Image Postprocessing70
IV. Geometric Knowledge-Based Systems Framework for Structural Image Analysis71
V. Fingerprint Image Postprocessing78
VI. Line Extraction and Junction Detection86
VII. Postprocessing Results and Discussion89
VIII. Conclusion96
References101
Chapter 4. Intensive Knowledge-Based Enterprise Modelling103
I. Introduction104
II. Review of Intelligent Techniques104
III. Characteristics of Intensive Knowledge106
IV. Intensive Knowledge Engineering107
V. Enterprise Modelling Based on Intensive Knowledge Engineering111
VI. Activity Formalism113
VII. The Business Process119
VIII. Conclusion121
References122
Chapter 5. Communication Model for Module-Based Knowledge Systems125
I. Introduction125
II. Existing Approaches to Communication127
III. Review of Open Intelligent Information Systems Architecture128
IV. Fundamentals of the Communication Model130
V. Prototype Case141
VI. Conclusions146
References147
Chapter 6. Using Knowledge Distribution in Requirements Engineering149
I. Introduction150
II. Natural and Artificial Knowledge in Requirements Engineering152
III. Notion of Knowledge Distribution161
IV. Types of Artificial Knowledge to Be Distributed165
V. Case Tool Diagrams and Structural Modelling for Generation of Additional Knowledge to Be Distribu169
VI. Conclusions182
References183
Chapter 7. A Universal Representation Paradigm for Knowledge Base Structuring Methods185
I. Introduction186
II. Complexity Issues Pertaining to the Classification of Knowledge Objects187
III. Classifiers Universal Paradigm: A Universal Representation Paradigm for Data-Driven Knowledge B189
IV. The Method of Structuring by Generalizations192
V. Further Refinement on the Classifiers Universal Paradigm197
VI. Conclusion and Future Research198
References199
Chapter 8. Database Systems Techniques and Tools in Automatic Knowledge Acquisition for Rule-Based E201
I. Introduction202
II. Data Quality Improvement205
III. Applications of Database Discovery Tools and Techniques in Expert System Development216
IV. Knowledge Validation Process223
V. Integrating Discovered Rules with Existing Rules240
VI. Issues and Concerns in Automatic Knowledge Acquisition242
VII. Conclusion and Future Direction244
References246
Chapter 9. Knowledge Acquisition via Bottom-Up Learning249
I. Introduction250
II. Review of Human Bottom-Up Skill Learning252
III. Model of Bottom-Up Skill Learning257
IV. Analysis of Bottom-Up Skill Learning265
V. General Discussion279
VI. Conclusion284
Appendix: Algorithmic Details of the Model285
References287
Chapter 10. Acquiring and Assessing Knowledge from Multiple Experts Using Graphical Representations293
I. Introduction294
II. Acquiring Knowledge from Multiple Experts298
III. Assessing Knowledge from Multiple Experts306
IV. Network Inference Approach to Knowledge Acquisition from Multiple Experts311
V. Closing Remarks321
References322
Chapter 11. Treating Uncertain Knowledge-Based Databases327
I. Introduction327
II. Overview of Related Techniques to Tackle Uncertainties in Knowledge-Based Databases329
III. Preliminaries336
IV. Techniques for Tackling Uncertainties in Knowledge-Based Databases338
V. Conclusion349
References350
Chapter 12. Geometric Knowledge-Based Systems Framework for Fingerprint Image Classification353
I. Introduction354
II. Previous Fingerprint Classification Work355
III. Comparison of Geometric Knowledge-Based Systems Framework with Previous Work356
IV. Geometric Grouping for Classification357
V. Geometric Knowledge-Based Systems Framework for Fingerprint Classification362
VI. Classification Results and Discussion369
Appendix: List of Symbols377
References378
Chapter 13. Geometric Knowledge-Based Systems Framework for Stereo Image Matching379
I. Introduction380
II. Constraints and Paradigms in Stereo Image Matching381
III. Edge-Based Stereo Image Matching382
IV. Geometric Knowledge-Based Systems Framework for Stereo Image Matching385
V. Matching Results and Discussion394
Appendix: List of Symbols407
References407
Chapter 14. Data Mining and Deductive Databases409
I. Introduction410
II. Data Mining and Deductive Databases410
III. Discovering Characteristic Rules from Large Deduction Results414
IV. Database Compression422
V. Conclusion432
References432
Chapter 15. Knowledge Discovery from Unsupervised Data in Support of Decision Making435
I. Introduction435
II. Knowledge Discovery and Data Mining436
III. Unsupervised Knowledge Discovery439
IV. Osham Method and System443
V. Conclusion459
References459
Chapter 16. Knowledge Processing in Control Systems463
I. Introduction464
II. Intelligent Systems and Control465
III. System Architecture467
IV. Distributed Traffic Control System475
V. System Implementation482
VI. Results489
VII. Conclusions492
Appendix: The Specification Language493
References495
Chapter 17. Using Domain Knowledge in Knowledge Discovery: An Optimization Perspective497
I. Introduction498
II. Overview of Knowledge Discovery501
III. Problems in Knowledge Discovery in Databases505
IV. Approaches to the Optimization of the Discovery Process509
V. Using Domain Knowledge in Knowledge Discovery513
VI. Conclusion and Future Direction531
References532
Chapter 18. Dynamic Structuring of Intelligent Computer Control Systems535
I. Introduction536
II. Multiagent Control Systems537
III. Knowledge Models and Representations for Computer Control Systems538
IV. Implementing Dynamic Structuring in Distributed Computer Control Systems548
V. Experimental Systems550
VI. Conclusion554
References555
Chapter 19. The Dynamic Construction of Knowledge-Based Systems559
I. Introduction560
II. Dynamic Construction of Knowledge-Based Systems569
III. Examples582
IV. Discussion597
V. Conclusion603
References604
Chapter 20. Petri Nets in Knowledge Verification and Validation of Rule-Based Expert Systems607
I. Preliminary608
II. Petri Net Models for Rule-Based Expert Systems610
III. Modeling Rule-Based Expert Systems with Enhanced High-Level Petri Nets617
IV. Tasks in Knowledge Verification and Validation622
V. Knowledge Verification and Validation as Reachability Problems in Enhanced High-Level Petri Nets624
VI. Matrix Approach629
VII. A Theorem Proving Approach637
VIII. Related Work647
IX. Concluding Remarks648
References649
Chapter 21. Assembling Techniques for Building Knowledge-Based Systems653
I. Introduction654
II. Background655
III. Prerequisites to Assembly659
IV. Assembly Techniques666
V. Applications of the Assembling Technique672
References674
Chapter 22. Self-Learning Knowledge Systems and Fuzzy Systems and Their Applications675
I. Introduction676
II. Overview677
III. Self-Learning Fuzzy Control Systems690
IV. Applications696
V. Adaptive-Network-Based Fuzzy Logic Controller Power System Stabilizers698
VI. Test Results701
VII. Conclusions703
Appendix704
References706
Chapter 23. Knowledge Learning Systems Techniques Utilizing Neurosystems and Their Application to Po709
I. Introduction710
II. Generic Neuro-Expert System Model710
III. Implementation714
IV. Training Neural Networks718
V. Conclusion727
References727
Chapter 24. Assembly Systems729
I. Knowledge Engineering730
II. Knowledge-Based Selection of Orienting Devices for Vibratory Bowl Feeders„A Case Study734
III. Conclusion752
References753
Chapter 25. Knowledge-Based Hybrid Techniques Combined with Simulation: Application to Robust Manufa755
I. Introduction756
II. Knowledge-Based Hybrid Systems757
III. Knowledge-Based Simulation764
IV. Combining Simulation, KBS, and Ann for Robust Manufacturing System Reconfiguration767
V. Combining Simulation and KBSs for Holonic Manufacturing780
VI. Conclusions787
References787
Chapter 26. Performance Evaluation and Tuning of UNIX-Based Software Systems791
I. Introduction792
II. Development Methodology792
III. Development of the System796
IV. Future Enhancements802
V. Conclusion803
References806
Chapter 27. Case-Based Reasoning807
I. Introduction807
II. Techniques809
III. Applications820
IV. Issues and Future Research831
V. Conclusion832
References833
Chapter 28. Production Planning and Control with Learning Technologies: Simulation and Optimization839
I. Introduction840
II. Global Competition and Consequences841
III. Order Management instead of PPC846
IV. Rough Planning in the Semi-conductor Industry854
V. Iterative Rough Planning with Artificial Neural Networks866
VI. Method Implementation878
VII. Summary885
References886
Chapter 29. Learning and Tuning Fuzzy Rule-Based Systems for Linguistic Modeling889
I. Introduction890
II. Fuzzy Rule-Based Systems891
III. Learning of Linguistic Fuzzy Rule-Based Systems899
IV. Tuning of Linguistic Fuzzy Rule-Based Systems919
V. Examples of Application: Experiments Developed and Results Obtained920
VI. Concluding Remarks927
Appendix I: Neural Networks928
Appendix II: Genetic Algorithms934
References938
Chapter 30. Knowledge Learning Techniques for Discrete Time Control Systems943
I. Introduction943
II. High-Order Discrete-Time Learning Control for Uncertain Discrete- Time Nonlinear Systems with Fe945
III. Terminal High-Order Iterative Learning Control964
IV. Conclusions975
References975
Chapter 31. Automatic Learning Approaches for Electric Power Systems977
I. Introduction977
II. Framework979
III. Automatic Learning Methods988
IV. Applications in Power Systems1020
V. Conclusions1033
References1034
Chapter 32. Design Knowledge Development for Productivity Enhancement in Concurrent Systems Design1037
I. Enhancing Design Productivity in Concurrent Systems Design1038
II. Our Technology Base1041
III. The Robust Concept Exploration Method1046
IV. High-Speed Civil Transport Design Using the Robust Concept Exploration Method1050
V. Conclusion1058
References1059
Chapter 33. Expert Systems in Power Systems Control1061
I. Introduction1061
II. A Paper Search on Expert Systems in Modern Energy Management Systems1074
III. A Trio of Expert Systems Developed and Used in Energy Management Systems1082
IV. Conclusions1102
References1106
Chapter 34. A Knowledge Modeling Technique for Construction of Knowledge and Databases1109
I. Introduction1109
II. The Inferential Model1113
III. Application of the IMT to the Solvent Selection for CO2 Separation Domain1117
IV. Application of the IMT to the Monitoring and Control of the Water Distribution System Problem Do1130
V. Conclusion1139
References1140
Chapter 35. The Representation of Positional Information1143
I. Introduction1144
II. A Qualitative Approach to Orientation1146
III. A Qualitative Approach to Distance1153
IV. Reasoning about Positional Information1163
V. Related Work1176
VI. Discussion and Future Research1183
References1184
Chapter 36. Petri Net Models in the Restoration of Power Systems Following System Collapse1189
I. Introduction1190
II. Basic Notions of Petri Nets1192
III. Dynamic Behavior and Verification of Properties of H-EPN Models for PSR1194
IV. Power System Restoration Process and H-EPN Methodology1197
V. Analysis and Simulation Results1201
VI. Discussion of the Applied H-EPN Approach1218
VII. Conclusions1222
Appendix1222
References1223
Chapter 37. The Development of VLSI Systems1227
I. Introduction1228
II. The Agents System1231
III. Software Agents as Objects1232
IV. Software Agents as Servers1240
V. Placement1243
VI. Routing1253
VII. The Placement/Routing Cycle1267
VIII. Conclusion1269
References1270
Chapter 38. Expert Systems in Foundry Operations1273
I. Introduction1274
II. Foundry Applications1278
III. Techniques for Developing Foundry Expert Systems1285
IV. Conclusions1290
References1290
Chapter 39. Knowledge-Based Systems in Scheduling1293
I. Introduction1293
II. Scheduling Examples1295
III. Representation of Scheduling Problems1301
IV. Scheduling Techniques1302
V. Knowledge-Based Scheduling Systems1313
VI. Research Areas1318
VII. Conclusion1322
References1322
Chapter 40. The Integration and Visualization of Assembly Sequences in Manufacturing Systems1327
I. Introduction1327
II. Review of Related Work1329
III. Assembly Modeling and Representation1333
IV. Assembly Sequence Generation and Visualization1362
V. Integrated Knowledge-Based Assembly Planning System1376
VI. Conclusions1396
References1397
Chapter 41. Knowledge-Based Decision Support Techniques and Their Application in Transportation Plan1403
I. Overview of Knowledge-Based Systems1404
II. Use of Knowledge-Based Systems in Transportation1407
III. Knowledge-Based Decision Support System Tool1410
IV. Conclusions and Further Research1424
Appendix1426
References1428
Index1431

Book details

Vendor Elsevier S & T
SKU 9780124438750
ISBN-13 9780080535289
Author Leondes, Cornelius T.
Category Computers
Subject Expert Systems

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The design of knowledge systems is finding myriad applications from corporate databases to general decision support in areas as diverse as engineering, manufacturing and other industrial processes, medicine, business, and economics. In engineering, for example, knowledge bases can be utilized for reliable electric power system operation. In medicine they support complex diagnoses, while in business they inform the process of strategic planning. Programmed securities trading and the defeat of chess champion Kasparov by IBM's Big Blue are two familiar examples of dedicated knowledge bases in combination with an expert system for decision-making.
With volumes covering "Implementation," "Optimization," "Computer Techniques," and "Systems and Applications," this comprehensive set constitutes a unique reference source for students, practitioners, and researchers in computer science, engineering, and the broad range of applications areas for knowledge-based systems.

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