Granular computing: An introduction
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| Main Author: | |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Boston u.a.
Kluwer Academic Publishers
2003
|
| Series: | The Kluwer international series in engineering and computer science
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| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Physical Description: | XVII, 452 S. graph. Darst. |
| ISBN: | 9781402072734 |
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| 245 | 1 | 0 | |a Granular computing |b An introduction |c Andrzej Bargiela ; Witold Pedrycz |
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| adam_text | GRANULAR COMPUTING AN INTRODUCTION BY ANDRZEJ BARGIELA THE NOTTINGHAM
TRENT UNIVERSITY NOTTINGHAM, UNITED KINGDOM WITOLD PEDRYCZ UNIVERSITY OF
ALBERTA EDMONTON, AB, CANADA KLUWER ACADEMIC PUBLISHERS BOSTON /
DORDRECHT / LONDON CONTENTS PREFACE XV PART I - METHODOLOGY AND
MATHEMATICAL FRAMEWORK CHAPTER 1 GRANULAR COMPUTING AS AN EMERGING
PRARDIGM OF INFORMATION PROCESSING 1 1.1 INTRODUCTORY COMMENTS 1 1.2
INFORMATION GRANULES ARE EVERYWHERE 1 SPATIAL GRANULATION: IMAGE
PROCESSING AND GIS 2 TEMPORAL GRANULATION 2 1.3 FORMAL MODELS OF
INFORMATION GRANULES 5 1.4 CONCEPTUAL ASPECTS OF INFORMATION GRANULES 6
SIZE OF INFORMATION GRANULES AND THEIR RELEVANCE 6 USEFULNESS OF
INFORMATION GRANULES 7 1.5 DEFINING A GRANULAR WORLD 8 1.6 GRANULAR
COMPUTING: AN INFORMATION PROCESSING PYRAMID 9 1.7 COMMUNICATION BETWEEN
GRANULAR WORLDS 11 FUNDAMENTAL ISSUES OF TRAVERSING INFORMATION PYRAMID:
ENCODING AND DECODING 12 INTEROPERABILITY BETWEEN DIFFERENT FORMAL
PLATFORMS OF INFORMATION GRANULES 1 5 1.8 CONCLUSIONS 17 REFERENCES 17
CHAPTER 2 SETS AND INTERVALS 19 2.1 HISTORICAL BACKGROUND 19 2.2 THE
FORMALISM OF SETS 22 BASIC SET OPERATIONS 23 FUNCTIONAL MAPPING OF SETS
25 ARITHMETICAL OPERATIONS ON SETS 27 2.3 SET ENCLOSURE 27 2.4 INTERVAL
ANALYSIS 29 BASIC INTERVAL OPERATIONS 29 ARITHMETICAL OPERATIONS ON
INTERVALS 32 2.5 INTERVAL VECTORS 34 VIII CONTENTS 2.6 INTERVAL MATRICES
36 2.7 ENCLOSURE OF FUNCTIONS 40 CENTERED ENCLOSURES 41 SPACE
SUBDIVISION ENCLOSURES 42 2.8 CONCLUSIONS 44 REFERENCES 45 CHAPTER 3
FUZZY SETS 47 3.1 THE CONCEPT AND FORMALISM 47 3.2 THE DESCRIPTION AND
GEOMETRY OF FUZZY SETS 51 3.3 MAIN CLASSES OF MEMBERSHIP FUNCTIONS 54
3.4 OPERATIONS ON FUZZY SETS 58 3.5 INFORMATION GRANULARITY AND FUZZY
SETS 62 3.6 RELATIONSHIPS BETWEEN FUZZY SETS IN THE SAME SPACE 65 3.7
FUZZY SETS AND LINGUISTIC VARIABLES 66 3.8 TRANSFORMATIONS OF FUZZY SETS
IN THE SAME SPACE 67 3.9 FUZZY ARITHMETIC 69 3.10 FUZZY RELATIONS AND
RELATIONAL CALCULUS 71 3.11 FUZZY SETS AND MULTIVALUED LOGIC 74 3.12
CALIBRATION OF FUZZY SETS 75 3.13 THE EMBEDDING PRINCIPLE 76 3.14
CONCLUSIONS 77 REFERENCES 78 CHAPTER 4 ROUGH SETS 81 4.1 INTRODUCTION 81
4.2 THE CONCEPT 81 4.3 INFORMATION SYSTEMS 84 4.4 ROUGH SETS AS SET
APPROXIMATIONS 87 4.5 CHARACTERIZATION OF ROUGH SETS 88 4.6 SET
COMPARISONS IN THE SETTING OF ROUGH SETS 90 4.7 REDUCTION OF ATTRIBUTE
SPACES AND REDUCTS 92 4.8 ROUGH FUNCTIONS 93 4.9 CONCLUSIONS 95
REFERENCES 96 CHAPTER 5 GENERALISATIONS OF INFORMATION GRANULES 99 5.1
INTERVAL-VALUED FUZZY SETS 99 5.2 FUZZY SETS OF TYPE-2 AND HIGHER ORDERS
101 5.3 FUZZY SETS OF LEVEL-2 AND HIGHER 103 5.4 FUZZY SETS AND ROUGH
SETS 104 5.5 SHADOWED SETS 107 OPERATIONS ON SHADOWED SETS 112
TRANSFORMATIONS OF SHADOWED SETS 113 CONTENTS IX 5.6 PROBABILISTIC SETS
114 5.7 INTUITIONISTIC FUZZY SETS 115 5.8 PROBABILITY OF GRANULAR
CONSTRUCTS: GRANULARITY AND THEIR EXPERIMENTAL RELEVANCE 119 5.9
CONCLUDING COMMENTS 123 REFERENCES 123 PART II - ALGORITHMS OF
INFORMATION GRANULATION CHAPTER 6 FROM NUMBERS TO INFORMATION GRANULES
125 6.1 INTRODUCTORY COMMENTS 125 6.2 INFORMATION GRANULES AND
INFORMATION GRANULATION 126 6.3 THE PRINCIPLE OF GRANULAR CLUSTERING 128
CONCEPTUAL DESIGN 128 INTERPRETATION AND VALIDATION OF GRANULAR
CLUSTERING 130 6.4 THE COMPUTATIONAL ASPECTS OF GRANULAR COMPUTING 131
DEFINING COMPATIBILITY BETWEEN INFORMATION GRANULES 131 EXPRESSING
INCLUSION OF INFORMATION GRANULES 139 6.5 THE GRANULAR ANALYSIS 141
CHARACTERIZATION OF HYPERBOXES 142 GRANULAR FEATURE ANALYSIS 142 6.6
EXPERIMENTAL STUDIES 144 SYNTHETIC DATA 144 BOSTON HOUSING DATA 151 6.7
CONCLUSIONS 158 REFERENCES 159 CHAPTER 7 RECURSIVE INFORMATION
GRANULATION 161 7.1 INTRODUCTION 161 7.2 EXAMPLE APPLICATION DOMAINS 162
7.3 INFORMATION GRANULES: DESIGN AND CHARACTERIZATION 164 BUILDING
SET-BASED INFORMATION GRANULES 164 7.4 ASSESSMENT AND INTERPRETATION OF
INFORMATION GRANULE THROUGH FUZZY CLUSTERING 174 7.5 GRANULAR TIME
SERIES 179 TIME-DOMAIN GRANULATION 179 PHASE-SPACE GRANULATION 183 7.6
NUMERICAL STUDIES 184 7.7 CONCLUSIONS 190 REFERENCES 190 CONTENTS
CHAPTER 8 GRANULAR PROTOTYPING IN FUZZY CLUSTERING 193 8.1 INTRODUCTION
193 8.2 PROBLEM FORMULATION 194 EXPRESSING SIMILARITY BETWEEN TWO FUZZY
SETS 194 PERFORMANCE INDEX (OBJECTIVE FUNCTION) 196 8.3 PROTOTYPE
OPTIMISATION 198 8.4 THE DEVELOPMENT OF GRANULAR PROTOTYPES 208
OPTIMIZATION OF THE SIMILARITY LEVELS 209 AN INVERSE SIMILARITY PROBLEM
210 8.5 CONCLUSIONS 213 REFERENCES 214, CHAPTER 9 LOGIC-BASED FUZZY
CLUSTERING 217 9.1 INTRODUCTION AND PROBLEM FORMULATION 217 9.2 THE
ALGORITHM 219 9.3 EXPERIMENTAL STUDIES 226 9.4 CONCLUSIONS 232
REFERENCES 232 CHAPTER 10 SEMANTICAL STABILITY OF INFORMATION GRANULES
235 10.1 INTRODUCTION 235 10.2 INFORMATION GRANULATION: DESIGN AND
VALIDATION 237 10.3 SET APPROXIMATION OF FUZZY SETS 239 10.4 ALGORITHMIC
ISSUES OF INFORMATION GRANULATION: DESIGN AND VALIDATION 241 THE DESIGN
OF FUZZY SETS - INFORMATION GRANULES 241 THE VALIDATION PHASE 244 10.5
EXPERIMENTS 245 SYNTHETIC ONE-DIMENSIONAL DATA 245 /?EA/-WORLD DATA 248
10.6 CONCLUSIONS 253 REFERENCES 253 PART III - GRANULAR WORLD
COMMUNICATIONS CHAPTER 11 COMMUNICATIONS BETWEEN GRANULAR WORLDS:
FUNDAMENTALS 255 11.1 INTRODUCTION 255 11.2 REPRESENTATION OF FUZZY SETS
IN THE SET-THEORETIC FRAMEWORK 256 11.3 COMMUNICATION WITH A NUMERIC
WORLD 261 11.4 CONCLUSIONS 265 REFERENCES 265 CONTENTS XI CHAPTER 12
NETWORKING OF GRANULAR WORLDS: COLLABORATIVE CLUSTERING 267 12.1
INTRODUCTION 267 12.2 THE HORIZONTAL COLLABORATIVE CLUSTERING 270 THE
NOTATION 270 OPTIMIZATION DETAILS OF THE COLLABORATIVE CLUSTERING 273
THE DETAILED CLUSTERING ALGORITHM: A FLOW OF COMPUTING 275
QUANTIFICATION OF THE COLLABORATIVE PHENOMENON OF THE CLUSTERING 276
NUMERICAL EXAMPLES OF HORIZONTAL COLLABORATION 277 12.3 VERTICAL
COLLABORATIVE CLUSTERING 284 THE CLUSTERING ALGORITHM 284 NUMERICAL
EXPERIMENTS WITH VERTICAL COLLABORATION 289 12.4 VERTICAL AND HORIZONTAL
CLUSTERING: COLLABORATION SPACE AND DATA CONFIDENTIALITY AND SECURITY
295 12.5 CONCLUSIONS 298 REFERENCES 299 CHAPTER 13 DIRECTIONAL MODELS OF
GRANULAR COMMUNICATION 301 13.1 INTRODUCTION 301 13.2 PROBLEM
FORMULATION 302 THE OBJECTIVE FUNCTION AND ITS GENERALIZATION 303 THE
LOGIC TRANSFORMATION 304 13.3 THE ALGORITHM 306 13.4 THE OVERALL
DEVELOPMENT FRAMEWORK: A FLOW OF OPTIMISATION ACTIVITIES 309 13.5
EXPERIMENTAL STUDIES 310 13.6 CONCLUSIONS 321 REFERENCES 322 CHAPTER 14
INTELLIGENT AGENTS AND GRANULAR WORLDS 323 14.1 INTRODUCTION 323 14.2
COMMUNICATION BETWEEN THE AGENTS IN THE GRANULAR ENVIRONMENT 324 14.3 A
FUZZY STATE MACHINE AS A GENERIC MODEL OF AN INTELLIGENT AGENT 328 14.4
THE FUZZY JK FLIP-FLOP AND ITS DYNAMICS 330 14.5 THE DEVELOPMENT OF
MOORE TYPE FUZZY STATE MACHINES 334 THE ARCHITECTURE 334 A LOGIC
PROCESSOR AND ITS DETAILED TOPOLOGY 335 A FUZZY MOORE STATE MACHINE 337
14.6 THE LEARNING SCHEME 337 14.7 CONCLUSIONS 346 REFERENCES 347 XII
CONTENTS PART IV - GRANULAR SYSTEMS APPLICATIONS CHAPTER 15
SELF-ORGANISING MAPS IN THE DESIGN AND PROCESSING OF GRANULAR
INFORMATION 349 15.1 INTRODUCTION 349 15.2 SELF-ORGANIZING MAPS 349
REVEALING STRUCTURE IN DATA BY CLUSTER GROWING 354 15.3 ASSOCIATED
SELF-ORGANIZING MAPS 355 WEIGHT MAPS 355 REGION (CLUSTERING) MAP 356
DATA DISTRIBUTION MAP 357 15.4 EXPERIMENTS - SYNTHETIC AND MACHINE
LEARNING DATA 358 15.5 CASE STUDY: ANALYSIS OF SOFTWARE QUALITY VIA
SOFTWARE MEASURES 364 SOFTWARE MEASURES 365 VISUALISING RELATIONSHIPS
BETWEEN SOFTWARE MEASURES WITH SOMS 365 15.6 CASE STUDY: A GRANULAR
ANALYSIS OF ECG DATA 369 15.7 CONCLUSIONS 375 REFERENCES 376 CHAPTER 16
TEMPORAL GRANULATION AND SIGNAL ANALYSIS 377 16.1 INTRODUCTORY NOTES 377
16.2 GRANULATION OF SIGNALS IN SPATIAL DOMAIN 378 THE DEVELOPMENT OF
DATA-JUSTIFIABLE INFORMATION GRANULES: AFORMULATION 378 16.3 THE
DETAILED GRANULATION ALGORITHM 380 16.4 GRANULAR MODELS OF SIGNALS 3 87
PREDICTIVE DESCRIPTION OF GRANULAR MODELS 388 CONDENSATION OF NUMERIC
SIGNALS 388 16.5 EXPERIMENTAL STUDIES , 389 16.6 ROUGH SETS IN SIGNAL
GRANULATION 395 16.7 CONCLUSIONS 396 REFERENCES 397 CHAPTER 17 -
GRANULAR DATA COMPRESSION 399 17.1 INTRODUCTION 399 17.2 FUZZY
RELATIONAL EQUATIONS: A BRIEF OVERVIEW 399 17.3 RELATIONAL CALCULUS IN
IMAGE COMPRESSION 402 17.4 EXPERIMENTS 407 17.5 CONCLUSIONS 415
REFERENCES 416 CONTENTS XIII CHAPTER 18 INTERVAL STATE ESTIMATION IN
SYSTEMS MODELLING 18.1 INTRODUCTION 18.2 ESTIMATION OF THE STATE
UNCERTAINTY SET MONTE CARLO METHOD LINEAR PROGRAMMING METHOD ELLIPSOID
METHOD SENSITIVITY MATRIX METHOD 18.3 REAL-LIFE APPLICATION 18.4
CONCLUSIONS REFERENCES EPILOGUE INDEX 417 417 419 421 422 427 433 436
443 444 447 449
|
| adam_txt |
GRANULAR COMPUTING AN INTRODUCTION BY ANDRZEJ BARGIELA THE NOTTINGHAM
TRENT UNIVERSITY NOTTINGHAM, UNITED KINGDOM WITOLD PEDRYCZ UNIVERSITY OF
ALBERTA EDMONTON, AB, CANADA KLUWER ACADEMIC PUBLISHERS BOSTON /
DORDRECHT / LONDON CONTENTS PREFACE XV PART I - METHODOLOGY AND
MATHEMATICAL FRAMEWORK CHAPTER 1 GRANULAR COMPUTING AS AN EMERGING
PRARDIGM OF INFORMATION PROCESSING 1 1.1 INTRODUCTORY COMMENTS 1 1.2
INFORMATION GRANULES ARE EVERYWHERE 1 SPATIAL GRANULATION: IMAGE
PROCESSING AND GIS 2 TEMPORAL GRANULATION 2 1.3 FORMAL MODELS OF
INFORMATION GRANULES 5 1.4 CONCEPTUAL ASPECTS OF INFORMATION GRANULES 6
SIZE OF INFORMATION GRANULES AND THEIR RELEVANCE 6 USEFULNESS OF
INFORMATION GRANULES 7 1.5 DEFINING A GRANULAR WORLD 8 1.6 GRANULAR
COMPUTING: AN INFORMATION PROCESSING PYRAMID 9 1.7 COMMUNICATION BETWEEN
GRANULAR WORLDS 11 FUNDAMENTAL ISSUES OF TRAVERSING INFORMATION PYRAMID:
ENCODING AND DECODING 12 INTEROPERABILITY BETWEEN DIFFERENT FORMAL
PLATFORMS OF INFORMATION GRANULES 1 5 1.8 CONCLUSIONS 17 REFERENCES 17
CHAPTER 2 SETS AND INTERVALS 19 2.1 HISTORICAL BACKGROUND 19 2.2 THE
FORMALISM OF SETS 22 BASIC SET OPERATIONS 23 FUNCTIONAL MAPPING OF SETS
25 ARITHMETICAL OPERATIONS ON SETS 27 2.3 SET ENCLOSURE 27 2.4 INTERVAL
ANALYSIS 29 BASIC INTERVAL OPERATIONS 29 ARITHMETICAL OPERATIONS ON
INTERVALS 32 2.5 INTERVAL VECTORS 34 VIII CONTENTS 2.6 INTERVAL MATRICES
36 2.7 ENCLOSURE OF FUNCTIONS 40 CENTERED ENCLOSURES 41 SPACE
SUBDIVISION ENCLOSURES 42 2.8 CONCLUSIONS 44 REFERENCES 45 CHAPTER 3
FUZZY SETS 47 3.1 THE CONCEPT AND FORMALISM 47 3.2 THE DESCRIPTION AND
GEOMETRY OF FUZZY SETS 51 3.3 MAIN CLASSES OF MEMBERSHIP FUNCTIONS 54
3.4 OPERATIONS ON FUZZY SETS 58 3.5 INFORMATION GRANULARITY AND FUZZY
SETS 62 3.6 RELATIONSHIPS BETWEEN FUZZY SETS IN THE SAME SPACE 65 3.7
FUZZY SETS AND LINGUISTIC VARIABLES 66 3.8 TRANSFORMATIONS OF FUZZY SETS
IN THE SAME SPACE 67 3.9 FUZZY ARITHMETIC 69 3.10 FUZZY RELATIONS AND
RELATIONAL CALCULUS 71 3.11 FUZZY SETS AND MULTIVALUED LOGIC 74 3.12
CALIBRATION OF FUZZY SETS 75 3.13 THE EMBEDDING PRINCIPLE 76 3.14
CONCLUSIONS 77 REFERENCES 78 CHAPTER 4 ROUGH SETS 81 4.1 INTRODUCTION 81
4.2 THE CONCEPT 81 4.3 INFORMATION SYSTEMS 84 4.4 ROUGH SETS AS SET
APPROXIMATIONS 87 4.5 CHARACTERIZATION OF ROUGH SETS 88 4.6 SET
COMPARISONS IN THE SETTING OF ROUGH SETS 90 4.7 REDUCTION OF ATTRIBUTE
SPACES AND REDUCTS 92 4.8 ROUGH FUNCTIONS 93 4.9 CONCLUSIONS 95
REFERENCES 96 CHAPTER 5 GENERALISATIONS OF INFORMATION GRANULES 99 5.1
INTERVAL-VALUED FUZZY SETS 99 5.2 FUZZY SETS OF TYPE-2 AND HIGHER ORDERS
101 5.3 FUZZY SETS OF LEVEL-2 AND HIGHER 103 5.4 FUZZY SETS AND ROUGH
SETS 104 5.5 SHADOWED SETS 107 OPERATIONS ON SHADOWED SETS 112
TRANSFORMATIONS OF SHADOWED SETS 113 CONTENTS IX 5.6 PROBABILISTIC SETS
114 5.7 INTUITIONISTIC FUZZY SETS 115 5.8 PROBABILITY OF GRANULAR
CONSTRUCTS: GRANULARITY AND THEIR EXPERIMENTAL RELEVANCE 119 5.9
CONCLUDING COMMENTS 123 REFERENCES 123 PART II - ALGORITHMS OF
INFORMATION GRANULATION CHAPTER 6 FROM NUMBERS TO INFORMATION GRANULES
125 6.1 INTRODUCTORY COMMENTS 125 6.2 INFORMATION GRANULES AND
INFORMATION GRANULATION 126 6.3 THE PRINCIPLE OF GRANULAR CLUSTERING 128
CONCEPTUAL DESIGN 128 INTERPRETATION AND VALIDATION OF GRANULAR
CLUSTERING 130 6.4 THE COMPUTATIONAL ASPECTS OF GRANULAR COMPUTING 131
DEFINING COMPATIBILITY BETWEEN INFORMATION GRANULES 131 EXPRESSING
INCLUSION OF INFORMATION GRANULES 139 6.5 THE GRANULAR ANALYSIS 141
CHARACTERIZATION OF HYPERBOXES 142 GRANULAR FEATURE ANALYSIS 142 6.6
EXPERIMENTAL STUDIES 144 SYNTHETIC DATA 144 BOSTON HOUSING DATA 151 6.7
CONCLUSIONS 158 REFERENCES 159 CHAPTER 7 RECURSIVE INFORMATION
GRANULATION 161 7.1 INTRODUCTION 161 7.2 EXAMPLE APPLICATION DOMAINS 162
7.3 INFORMATION GRANULES: DESIGN AND CHARACTERIZATION 164 BUILDING
SET-BASED INFORMATION GRANULES 164 7.4 ASSESSMENT AND INTERPRETATION OF
INFORMATION GRANULE THROUGH FUZZY CLUSTERING 174 7.5 GRANULAR TIME
SERIES 179 TIME-DOMAIN GRANULATION 179 PHASE-SPACE GRANULATION 183 7.6
NUMERICAL STUDIES 184 7.7 CONCLUSIONS 190 REFERENCES 190 CONTENTS
CHAPTER 8 GRANULAR PROTOTYPING IN FUZZY CLUSTERING 193 8.1 INTRODUCTION
193 8.2 PROBLEM FORMULATION 194 EXPRESSING SIMILARITY BETWEEN TWO FUZZY
SETS 194 PERFORMANCE INDEX (OBJECTIVE FUNCTION) 196 8.3 PROTOTYPE
OPTIMISATION 198 8.4 THE DEVELOPMENT OF GRANULAR PROTOTYPES 208
OPTIMIZATION OF THE SIMILARITY LEVELS 209 AN INVERSE SIMILARITY PROBLEM
210 8.5 CONCLUSIONS 213 REFERENCES 214, CHAPTER 9 LOGIC-BASED FUZZY
CLUSTERING 217 9.1 INTRODUCTION AND PROBLEM FORMULATION 217 9.2 THE
ALGORITHM 219 9.3 EXPERIMENTAL STUDIES 226 9.4 CONCLUSIONS 232
REFERENCES 232 CHAPTER 10 SEMANTICAL STABILITY OF INFORMATION GRANULES
235 10.1 INTRODUCTION 235 10.2 INFORMATION GRANULATION: DESIGN AND
VALIDATION 237 10.3 SET APPROXIMATION OF FUZZY SETS 239 10.4 ALGORITHMIC
ISSUES OF INFORMATION GRANULATION: DESIGN AND VALIDATION 241 THE DESIGN
OF FUZZY SETS - INFORMATION GRANULES 241 THE VALIDATION PHASE 244 10.5
EXPERIMENTS 245 SYNTHETIC ONE-DIMENSIONAL DATA 245 /?EA/-WORLD DATA 248
10.6 CONCLUSIONS 253 REFERENCES " 253 PART III - GRANULAR WORLD
COMMUNICATIONS CHAPTER 11 COMMUNICATIONS BETWEEN GRANULAR WORLDS:
FUNDAMENTALS 255 11.1 INTRODUCTION 255 11.2 REPRESENTATION OF FUZZY SETS
IN THE SET-THEORETIC FRAMEWORK 256 11.3 COMMUNICATION WITH A NUMERIC
WORLD 261 11.4 CONCLUSIONS 265 REFERENCES 265 CONTENTS XI CHAPTER 12
NETWORKING OF GRANULAR WORLDS: COLLABORATIVE CLUSTERING 267 12.1
INTRODUCTION 267 12.2 THE HORIZONTAL COLLABORATIVE CLUSTERING 270 THE
NOTATION 270 OPTIMIZATION DETAILS OF THE COLLABORATIVE CLUSTERING 273
THE DETAILED CLUSTERING ALGORITHM: A FLOW OF COMPUTING 275
QUANTIFICATION OF THE COLLABORATIVE PHENOMENON OF THE CLUSTERING 276
NUMERICAL EXAMPLES OF HORIZONTAL COLLABORATION 277 12.3 VERTICAL
COLLABORATIVE CLUSTERING 284 THE CLUSTERING ALGORITHM 284 NUMERICAL
EXPERIMENTS WITH VERTICAL COLLABORATION 289 12.4 VERTICAL AND HORIZONTAL
CLUSTERING: COLLABORATION SPACE AND DATA CONFIDENTIALITY AND SECURITY
295 12.5 CONCLUSIONS 298 REFERENCES 299 CHAPTER 13 DIRECTIONAL MODELS OF
GRANULAR COMMUNICATION 301 13.1 INTRODUCTION 301 13.2 PROBLEM
FORMULATION 302 THE OBJECTIVE FUNCTION AND ITS GENERALIZATION 303 THE
LOGIC TRANSFORMATION 304 13.3 THE ALGORITHM 306 13.4 THE OVERALL
DEVELOPMENT FRAMEWORK: A FLOW OF OPTIMISATION ACTIVITIES 309 13.5
EXPERIMENTAL STUDIES 310 13.6 CONCLUSIONS 321 REFERENCES 322 CHAPTER 14
INTELLIGENT AGENTS AND GRANULAR WORLDS 323 14.1 INTRODUCTION 323 14.2
COMMUNICATION BETWEEN THE AGENTS IN THE GRANULAR ENVIRONMENT 324 14.3 A
FUZZY STATE MACHINE AS A GENERIC MODEL OF AN INTELLIGENT AGENT 328 14.4
THE FUZZY JK FLIP-FLOP AND ITS DYNAMICS 330 14.5 THE DEVELOPMENT OF
MOORE TYPE FUZZY STATE MACHINES 334 THE ARCHITECTURE 334 A LOGIC
PROCESSOR AND ITS DETAILED TOPOLOGY 335 A FUZZY MOORE STATE MACHINE 337
14.6 THE LEARNING SCHEME 337 14.7 CONCLUSIONS 346 REFERENCES 347 XII
CONTENTS PART IV - GRANULAR SYSTEMS APPLICATIONS CHAPTER 15
SELF-ORGANISING MAPS IN THE DESIGN AND PROCESSING OF GRANULAR
INFORMATION 349 15.1 INTRODUCTION 349 15.2 SELF-ORGANIZING MAPS 349
REVEALING STRUCTURE IN DATA BY CLUSTER GROWING 354 15.3 ASSOCIATED
SELF-ORGANIZING MAPS 355 WEIGHT MAPS 355 REGION (CLUSTERING) MAP 356
DATA DISTRIBUTION MAP 357 15.4 EXPERIMENTS - SYNTHETIC AND MACHINE
LEARNING DATA 358 15.5 CASE STUDY: ANALYSIS OF SOFTWARE QUALITY VIA
SOFTWARE MEASURES 364 SOFTWARE MEASURES 365 VISUALISING RELATIONSHIPS
BETWEEN SOFTWARE MEASURES WITH SOMS 365 15.6 CASE STUDY: A GRANULAR
ANALYSIS OF ECG DATA 369 15.7 CONCLUSIONS 375 REFERENCES 376 CHAPTER 16
TEMPORAL GRANULATION AND SIGNAL ANALYSIS 377 16.1 INTRODUCTORY NOTES 377
16.2 GRANULATION OF SIGNALS IN SPATIAL DOMAIN 378 THE DEVELOPMENT OF
DATA-JUSTIFIABLE INFORMATION GRANULES: AFORMULATION 378 16.3 THE
DETAILED GRANULATION ALGORITHM 380 16.4 GRANULAR MODELS OF SIGNALS 3 87
PREDICTIVE DESCRIPTION OF GRANULAR MODELS 388 CONDENSATION OF NUMERIC
SIGNALS 388 16.5 EXPERIMENTAL STUDIES , 389 16.6 ROUGH SETS IN SIGNAL
GRANULATION 395 16.7 CONCLUSIONS 396 REFERENCES 397 CHAPTER 17 -
GRANULAR DATA COMPRESSION 399 17.1 INTRODUCTION 399 17.2 FUZZY
RELATIONAL EQUATIONS: A BRIEF OVERVIEW 399 17.3 RELATIONAL CALCULUS IN
IMAGE COMPRESSION 402 17.4 EXPERIMENTS 407 17.5 CONCLUSIONS 415
REFERENCES 416 CONTENTS XIII CHAPTER 18 INTERVAL STATE ESTIMATION IN
SYSTEMS MODELLING 18.1 INTRODUCTION 18.2 ESTIMATION OF THE STATE
UNCERTAINTY SET MONTE CARLO METHOD LINEAR PROGRAMMING METHOD ELLIPSOID
METHOD SENSITIVITY MATRIX METHOD 18.3 REAL-LIFE APPLICATION 18.4
CONCLUSIONS REFERENCES EPILOGUE INDEX 417 417 419 421 422 427 433 436
443 444 447 449 |
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| author | Bargiela, Andrzej |
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| discipline_str_mv | Informatik |
| format | Book |
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| id | DE-604.BV021796435 |
| illustrated | Illustrated |
| index_date | 2024-07-02T15:46:19Z |
| indexdate | 2024-07-09T20:44:49Z |
| institution | BVB |
| isbn | 9781402072734 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-015009008 |
| oclc_num | 50717669 |
| open_access_boolean | |
| owner | DE-M347 |
| owner_facet | DE-M347 |
| physical | XVII, 452 S. graph. Darst. |
| publishDate | 2003 |
| publishDateSearch | 2003 |
| publishDateSort | 2003 |
| publisher | Kluwer Academic Publishers |
| record_format | marc |
| series2 | The Kluwer international series in engineering and computer science |
| spelling | Bargiela, Andrzej Verfasser aut Granular computing An introduction Andrzej Bargiela ; Witold Pedrycz Boston u.a. Kluwer Academic Publishers 2003 XVII, 452 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier The Kluwer international series in engineering and computer science Granular computing Pedrycz, Witold 1953- Sonstige (DE-588)122838203 oth GBV Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=015009008&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Bargiela, Andrzej Granular computing An introduction Granular computing |
| title | Granular computing An introduction |
| title_auth | Granular computing An introduction |
| title_exact_search | Granular computing An introduction |
| title_exact_search_txtP | Granular computing An introduction |
| title_full | Granular computing An introduction Andrzej Bargiela ; Witold Pedrycz |
| title_fullStr | Granular computing An introduction Andrzej Bargiela ; Witold Pedrycz |
| title_full_unstemmed | Granular computing An introduction Andrzej Bargiela ; Witold Pedrycz |
| title_short | Granular computing |
| title_sort | granular computing an introduction |
| title_sub | An introduction |
| topic | Granular computing |
| topic_facet | Granular computing |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=015009008&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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