Intelligent systems for engineering: a knowledge based approach
Saved in:
| Main Author: | |
|---|---|
| Format: | Book |
| Language: | German |
| Published: |
London [u.a.]
Springer
1997
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| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Physical Description: | XLII, 804 S. Ill., graph. Darst. |
| ISBN: | 3540761284 |
Staff View
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Record in the Search Index
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| adam_text | RAM D. SRIRAM INTELLIGENT SYSTEMS FOR ENGINEERING A KNOWLEDGE-BASED
APPROACH WITH 326 FIGURES SPRINGER CONTENTS PREFACE XXXI ACKNOWLEDGMENTS
XXXIX 1 KNOWLEDGE-BASED EXPERT SYSTEMS: AN OVERVIEW 1 1.1 INTRODUCTION 1
1.2 WELL-STRUCTURED VS. ILL-STRUCTURED PROBLEMS 3 1.3 ARCHITECTURE OF
KNOWLEDGE-BASED EXPERT SYS- TEMS 4 1.3.1 EXPLANATION FACILITY . 6 1.3.2
KNOWLEDGE ACQUISITION FACILITY 7 1.4 CONVENTIONAL PROGRAMS VS. KBES 8
1.5 AN EXAMPLE 8 1.6 LEVELS FOR DESCRIBING KBES 12 1.7 RANGE OF KBES
APPLICATIONS 15 1.8 PROBLEM SOLVING TECHNIQUES 19 1.9 TOOLS: PROGRAMMING
PARADIGMS 19 1.10 APPLICATIONS 23 1.10.1 DIAGNOSIS/CLASSIFICATION 23
1.10.2 MONITORING AND CONTROL 23 1.10.3 EDUCATION 24 1.10.4 PLANNING 24
1.10.5 DESIGN 25 VUEI CONTENTS 1.11 DEVELOPMENT OF A KBES 25 1.12
EPILOGUE 28 1.13 BIBLIOGRAPHIC NOTES 29 1.14 EXERCISES 30 1.15
REFERENCES . . 31 2 PROBLEM SOLVING: INTRODUCTION TO SEARCH METHODS 35
2.1 INTRODUCTION 36 2.2 PROBLEM SOLVING: A FORMAL INTERPRETATION ... 38
2.3 SEARCH METHODS: AN INTRODUCTION 41 2.4 SIMPLE SEARCH METHODS 45
2.4.1 DEPTH-FIRST SEARCH 45 2.4.2 BREADTH-FIRST SEARCH 52 2.4.3
DEPTH-FIRST METHOD VS. BREADTH-FIRST METHOD 56 2.5 EVALUATION-BASED
SEARCH 57 2.5.1 HILL CLIMBING: STEEPEST ASCENT 58 2.5.2 BEST-FIRST
SEARCH . 60 2.5.3 A* SEARCH 61 2.5.4 SIMULATED ANNEALING 71 2.5.5
GENETIC ALGORITHMS 78 2.6 SUMMARY N 90 2.7 BIBLIOGRAPHIC NOTES 93 2.8
EXERCISES 94 2.9 REFERENCES 97 3 KNOWLEDGE REPRESENTATION 103 3.1
INTRODUCTION 104 3.2 RULE-BASED REPRESENTATION 108 3.3 LOGIC 119 3.4
SEMANTIC NETWORKS 123 3.4.1 CLASSES OF NODES 123 3.4.2 CLASSES OF
RELATIONSHIPS 124 3.5 FRAMES 125 3.6 MODEL-BASED REPRESENTATION 133 3.7
MULTIPLE LEVELS OF REPRESENTATION 139 3.8 SUMMARY 144 3.9 BIBLIOGRAPHIC
NOTES 147 3.10 EXERCISES 148 3.11 REFERENCES 153 4 KNOWLEDGE-CENTERED
PROBLEM SOLVING STRATE- GIES 159 4.1 INTRODUCTION 160 4.2 FORWARD
CHAINING 160 CONTENTS IX 4.2.1 EXAMPLE OF FORWARD CHAINING 162 4.2.2 THE
RETE MATCH ALGORITHM 163 4.2.3 WHEN IS FORWARD CHAINING APPROPRIATE 172
4.3 BACKWARD CHAINING 172 4.4 THEOREM PROVING 173 4.5 GPS: MEANS-ENDS
ANALYSIS AND OPERATOR SUBGOAL- ING : 178 4.6 HEURISTIC-INC-GENERATE-TEST
178 4.7 HIERARCHICAL REFINEMENT 181 4.7.1 XCUT: AN AUTOMATED PROCESS
PLANNING SYSTEM .... 185 4.7.2 GHOST: A PROJECT NETWORK GENERATOR 188
4.7.3 PRIDE: PINCH ROLL INTERACTIVE DESIGN EXPERT 192 4.8
DEPENDENCY-DIRECTED BACKTRACKING AND TRUTH MAINTENANCE 193 4.9
CONSTRAINT HANDLING 199 4.9.1 SYMBOLIC CONSTRAINT PROCESSING . . . .
200 4.9.2 NUMERICAL CONSTRAINT PROCESSING 205 4.10 INEXACT INFERENCE
METHODS 210 4.11 SUMMARY 214 4.12 BIBLIOGRAPHIC NOTES 216 4.13 EXERCISES
217 4.14 REFERENCES 221 5 BLACKBOARD SYSTEMS 227 5.1 INTRODUCTION 227
5.2 BLACKBOARD SYSTEM^ AN OVERVIEW 229 5.3 HEARSAY-II 232 5.4 HASP/SIAP
234 5.5 BB1 APPLICATIONS 237 5.5.1 ERRAND PLANNING 239 5.5.2 SIGHTPLAN:
A CASE STUDY OF BB1 243 5.6 MODEL-BASED DIAGNOSIS: OOBB APPLICATION . .
. . 257 5.7 CONFIGURATION FOR MODEL-BASED DIAGNOSIS ... 263 5.7.1
INTRODUCTION 263 5.7.2 BLACKBOARD CONFIGURATION: PANEL TYPES 263 5.7.3
KNOWLEDGE SDFURCES 266 5.8 EXAMPLE OF MODEL-BASED DIAGNOSIS IN OOBB-MBD
270 5.9 SUMMARY 278 5.10 BIBLIOGRAPHIC NOTES 280 5.11 EXERCISES 280 5.12
REFERENCES 282 6 ANALOGICAL AND CASE-BASED REASONING 285 6.1
INTRODUCTION 285 CONTENTS 6.2 ANALOGY: BASICS 286 6.3 CASE-BASED
REASONING IN ENGINEERING DESIGN . . 290 6.4 ARCHITECTURE OF A CASE-BASED
REASONER 291 6.5 CASE-BASED REASONING EXAMPLES 298 6.5.1 CYCLOPS: A
CASE-BASED DESIGN DEBUGGER (PATCHING DESIGNS) 298 6.5.2 CADET: A
CASE-BASED BEHAVIORAL SYNTHESIS SYSTEM . . 311 6.5.3 PARAMETER
INSTANTIATION 323 6.6 SUMMARY , 325 6.7 BIBLIOGRAPHIC NOTES 326 6.8
EXERCISES 327 6.9 REFERENCES 329 QUALITATIVE REASONING 335 7.1
INTRODUCTION 336 7.2 CLASSIFICATION OF QUALITATIVE REASONING APPROACHES
344 7.3 QUALITATIVE MATHEMATICS 349 7.3.1 QUALITATIVE DERIVATIVES 352
7.3.2 SOLUTION TECHNIQUES FOR QUALITATIVE EQUATIONS 355 7.4 BEHAVIOR:
REPRESENTATION AND GENERATION ... 358 7.4.1 RULES FOR DETERMINING STATE
TRANSITIONS 358 7.4.2 MASS-SPRING SYSTEM REVISITED . . 361 7.5 DEVICE
CENTERED APPROACH 363 7.5.1 INTRODUCTION 363 7.5.2 DEVICE STRUCTURE 363
7.5.3 DEVICE MODEL 363 7.5.4 PREDICTING INTRA-STATE BEHAVIOR 366 7.5.5
PREDICTING INTER-STATE BEHAVIOR 366 7.6 QUALITATIVE PROCESS THEORY 369
7.6.1 REPRESENTATION OF OBJECTS 370 7.6.2 PROCESS REPRESENTATION 372
7.6.3 PREDICTING BEHAVIOR 374 7.6.4 MASS-SPRING EXAMPLE 376 7.7 QSIM 378
7.7.1 INTRODUCTION 378 7.7.2 QUANTITY SPACE OF QSIM 378 7.7.3
QUALITATIVE STATES 379 7.7.4 STATE TRANSITIONS 380 7.7.5 QUALITATIVE
CONSTRAINTS 382 7.7.6 THE QUALITATIVE SIMULATION ALGORITHM 385 7.7.7 THE
MASS-SPRING EXAMPLE 386 7.8 CRITICAL HYPERSURFACES 391 7.8.1
INTRODUCTION 391 7.8.2 AN EXAMPLE OF CRITICAL HYPERSURFACES 392 CONTENTS
7.8.3 THE SPACE OF HYPERSURFACES 393 7.8.4 THE COMPLETE RELEVANCE
PROBLEM 394 7.8.5 THE RELATIONSHIP PROBLEM 395 7.8.6 THE SEMANTICS
PROBLEM 397 7.8.7 EXAMPLE OF REASONING WITH CRITICAL HYPERSURFACES . . .
398 7.9 ORDER-OF-MAGNITUDE REASONING 400 7.9.1 INTRODUCTION 400 7.9.2 A
DESCRIPTION OF O[M] 401 7.9.3 SEMANTICS OF O[M] 403 7.9.4 ASSIGNMENTS,
CONSTRAINTS, AND RULES IN O[M] . . . . . . 408 7.9.5 HEAT EXCHANGER
EXAMPLE 411 7.10 QUALITATIVE GEOMETRIC RELATIONSHIPS 416 7.11
CONFIGURATION SPACES 421 7.11.1 INTRODUCTION 421 7.11.2 EXAMPLE: A CAM
MECHANISM 424 7.11.3 CONFIGURATION SPACES 425 7.11.4 REGION DIAGRAMS 426
7.11.5 CONFIGURATION SPACE COMPUTATION 427 7.11.6 PAIRWISE ANALYSIS 428
7.11.7 COMPOSITION 429 7.12 CAUSAL ORDERING 433 7.12.1 INTRODUCTION 433
7.12.2 THEORY OF CAUSAL ORDERING 433 7.12.3 EXAMPLE: A MIXED MODEL OF AN
EVAPORATOR 437 7.12.4 REASONING ABOUT BEHAVIOR 441 7.13 CASE STUDY:
TROUBLESHOOTING WITH QUALITATIVE REASONING 443 7.13.1 INTRODUCTION 443
7.13.2 MAINTENANCE AIDING APPROACHES 443 7.13.3 IMA OVERVIEW .444 7.13.4
A SIMPLE EXAMPLE 446 7.13.5 DIAGNOSTIC PERFORMANCE STUDY 449 7.13.6
RESULTS 451 7.13.7 MAINTENANCE TIME TO FAULT ISOLATE 452 7.13.8
DISCUSSION 453 7.13.9 DISCUSSION OF IMA 456 7.14 DISCUSSION AND SUMMARY
456 7.14.1 WHY QUALITATIVE SIMULATION 456 7.14.2 SHORTCOMINGS OF USING
QUALITATIVE SIMULATION ALONE . . 457 7.14.3 HISTORY OF QUALITATIVE
REASONING AND RESEARCH DIRECTIONS 458 7.14.4 SUMMARY OF APPROACHES
PRESENTED 459 7.15 BIBLIOGRAPHIC NOTES . 463 7.16 EXERCISES 464 7.17
REFERENCES 465 XII CONTENTS 8 NEURAL NETWORKS 471 8.1 INTRODUCTION 471
8.2 WHAT ARE NEURAL NETWORKS? 472 8.3 PATTERN RECOGNITION CONCEPTS 474
8.3.1 GOAL OF PATTERN RECOGNITION 475 8.3.2 FEATURE VECTORS AND FEATURE
SPACE 475 8.3.3 LINEAR CLASSIFIERS 476 8.3.4 LINEARLY SEPARABLE AND
INSEPARABLE PROBLEMS 477 8.3.5 NEAREST NEIGHBOR CLASSIFICATION 477 8.3.6
BAYESIAN CLASSIFIERS 478 8.4 THE ANATOMY OF A NEURAL NETWORK 479 8.4.1
SET OF PROCESSING UNITS 479 8.4.2 STATE OF ACTIVATION 481 8.4.3 OUTPUT
FUNCTION EMPLOYED 482 8.4.4 PATTERN OF CONNECTIVITY AMONG THE PROCESSING
UNITS . . 482 8.4.5 RULE OF PROPAGATION EMPLOYED 483 8.4.6 ACTIVATION
FUNCTION EMPLOYED 484 8.4.7 RULE OF LEARNING EMPLOYED 485 8.5 TYPES OF
NEURAL NETWORKS 486 8.5.1 BRIEF DESCRIPTION OF DIFFERENT TYPES OF
NETWORKS . . . . 486 8.5.2 PERCEPTRONS AND THE BACKPROPAGATION ALGORITHM
. . . . 490 8.6 CASE STUDIES IN ENGINEERING 504 8.6.1 CASE STUDY I:
USING ARTIFICIAL NEURAL NETWORKS TO LEARN TO RECOGNIZE PATTERNS IN
BIOPROCESS DATA 504 8.6.2 CASE STUDY 2: FAULT DIAGNOSIS OF CHEMICAL
PROCESS PLANTS USING NEURAL NETWORKS *..-... 517 8.7 DISCUSSION AND
SUMMARY 529 8.7.1 DISCUSSION 529 8.7.2 SUMMARY 530 8.8 BIBLIOGRAPHIC
NOTES 533 8.9 EXERCISES 534 8.10 REFERENCES 535 9 PROJECT MANAGEMENT 543
9.1 INTRODUCTION 543 9.2 COMPASS: KBES FOR TELEPHONE SWITCH MAINTE-
NANCE 544 9.3 KBES DEVELOPMENT CYCLE 547 9.3.1 IDENTIFICATION 548 9.3.2
CONCEPTUALIZATION 551 9.3.3 FORMALIZATION 552 9.3.4 IMPLEMENTATION 560
9.3.5 TESTING: VERIFICATION AND VALIDATION 562 9.4 KNOWLEDGE ACQUISITION
. . 565 9.4.1 MODES OF KNOWLEDGE ACQUISITION 566 CONTENTS XJUE 9.4.2
MANUAL TECHNIQUES 567 9.4.3 AUTOMATED TOOLS FOR KNOWLEDGE ACQUISITION
575 9.4.4 KNOWLEDGE ACQUISITION IN COMPASS 587 9.5 TECHNOLOGY TRANSFER
588 9.6 SUMMARY 590 9.7 BIBLIOGRAPHIC NOTES 592 9.8 EXERCISES 592 9.9
REFERENCES .594 10 KNOWLEDGE-BASED SYSTEM BUILDING TOOLS 601 10.1 COSMOS
602 10.1.1 THE COSMOS USER INTERFACE 604 10.1.2 EXAMPLE: USING THE
COSMOS 613 10.1.3 EMBEDDED COSMOS CODE 617 10.1.4 HOW TO OBTAIN COSMOS
618 10.2 KEE*:KNOWLEDGE ENGINEERING ENVIRONMENT . 618 10.2.1
INTRODUCTION 618 10.2.2 STRUCTURE OF A KEE KNOWLEDGE-BASE 619 10.2.3
SAMPLE PROBLEMS 622 10.3 KAPPA* 636 10.3.1 OBJECTS 636 10.3.2 RULES 638
10.3.3 CONTROL STRATEGIES 639 10.4 NEXPERT OBJECT* 640 10.4.1 OBJECTS
640 10.4.2 RULES : . . 642 10.4.3 CONTROL STRATEGIES 645 10.5
SMALLTALK-80: OBJECT-ORIENTED PROGRAMMING . 646 10.5.1 INTRODUCTION 646
10.5.2 FLOOR SYSTEM SYNTHESIS IMPLEMENTATION 650 10.6 G2*: A REAL-TIME
KBS TOOL 660 10.6.1 INTRODUCTION 660 10.6.2 GENERAL FRAMEWORK FOR
REAL-TIME KBES 660 10.6.3 INTERACTIVE WINDOWS, GRAPHICS AND ANIMATION
661 10.6.4 STRUCTURED ENGLISH EDITOR 662 10.6.5 FRAMES AND OBJECTS 662
10.6.6 CONNECTIONS, RELATIONS AND THE DIRECT MANIPULATION IN- TERFACE
662 10.6.7 FUNCTIONS AND PROCEDURES 664 10.6.8 REAL-TIME INFERENCE
ENGINE 664 10.6.9 THE G2 SIMULATOR 665 10.6.10 REAL-TIME SCHEDULER AND
OTHER TIME-RELATED FEATURES . 666 10.6.11 G2 AND NEURAL NETWORKS 667
10.7 CLASSIFICATION TOOLS: LOOM 667 10.8 SUMMARY 669 CONTENTS 10.9
APPENDLX: A BRIEF SUMMARY OF REPRESENTATIVE KBSTS . ! 670 10.10
REFERENCES 688 INEXACT INFERENCE TECHNIQUES 691 A.L INTRODUCTION 691 A.2
BAYESIAN APPROACH 692 A.3 CERTAINTY APPROACH 700 A.4 DEMPSTER-SHAFER
THEORY 706 A.5 FUZZY LOGIC . . 712 A.6 OTHER THEORIES 722 A.7 SUMMARY .
, 722 A.8 BIBLIOGRAPHIC NOTES 726 A.9 REFERENCES 726 MULTIPLE LEVELS IN
MECHANICAL DEVICE REPRE- SENTATION 729 B.L INTRODUCTION 729 B.2 DEVICE
STATICS 734 B.2.1 PHYSICAL STATES . . . 735 B.2.2 OBJECT REGIONS 736
B.2.3 OBJECT TYPES 739 B.2.4 PHYSICAL TYPE AND GEOMETRIE OBJECT
PRIMITIVES . . . . 740 B.2.5 OBJECT PRIMITIVES 743 B.2.6 OBJECT
CLASSIFICATION 743 B.2.7 DEVICES 749 B.2.8 DEVICE STATIC DESCRIPTIONS
750 B.3 LOW-LEVEL DYNAMICS: DEVICE BEHAVIOR 753 B.3.1 LOW-LEVEL OBJECT
BEHAVIOR 754 B.3.2 DEVICE BEHAVIOR SEQUENCES 761 B.4 HIGH-LEVEL
DYNAMICS: DEVICE FUNCTION 764 B.4.1 DEVICE FUNCTION : . . . . 766 B.4.2
MACHINE PRIMITIVES 769 B.5 DEVICE PRAGMATICS 777 B.5.1 DEVICE-USE PLANS
777 B.5.2 DEVICE USE GOALS 779 B.6 SUMMARY 787 INDEX 789
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| indexdate | 2024-07-09T18:08:07Z |
| institution | BVB |
| isbn | 3540761284 |
| language | German |
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| spelling | Sriram, Duvvuru 1957- Verfasser (DE-588)115617426 aut Intelligent systems for engineering a knowledge based approach Ram D. Sriram London [u.a.] Springer 1997 XLII, 804 S. Ill., graph. Darst. txt rdacontent n rdamedia nc rdacarrier Neuronales Netz (DE-588)4226127-2 gnd rswk-swf Wissensbasiertes System (DE-588)4197554-6 gnd rswk-swf Neuronales Netz (DE-588)4226127-2 s DE-604 Wissensbasiertes System (DE-588)4197554-6 s HEBIS Datenaustausch Darmstadt application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=007620806&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Sriram, Duvvuru 1957- Intelligent systems for engineering a knowledge based approach Neuronales Netz (DE-588)4226127-2 gnd Wissensbasiertes System (DE-588)4197554-6 gnd |
| subject_GND | (DE-588)4226127-2 (DE-588)4197554-6 |
| title | Intelligent systems for engineering a knowledge based approach |
| title_auth | Intelligent systems for engineering a knowledge based approach |
| title_exact_search | Intelligent systems for engineering a knowledge based approach |
| title_full | Intelligent systems for engineering a knowledge based approach Ram D. Sriram |
| title_fullStr | Intelligent systems for engineering a knowledge based approach Ram D. Sriram |
| title_full_unstemmed | Intelligent systems for engineering a knowledge based approach Ram D. Sriram |
| title_short | Intelligent systems for engineering |
| title_sort | intelligent systems for engineering a knowledge based approach |
| title_sub | a knowledge based approach |
| topic | Neuronales Netz (DE-588)4226127-2 gnd Wissensbasiertes System (DE-588)4197554-6 gnd |
| topic_facet | Neuronales Netz Wissensbasiertes System |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=007620806&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT sriramduvvuru intelligentsystemsforengineeringaknowledgebasedapproach |