Gespeichert in:
| Titel: | Tree-structure based hybrid computational intelligence theoretical foundations and applications |
|---|---|
| Von: |
Yuehui Chen and Ajith Abraham
|
| Person: |
Chen, Yuehui
1964- Verfasser aut Abraham, Ajith 1968- |
| Hauptverfassende: | , |
| Format: | Buch |
| Sprache: | Englisch |
| Veröffentlicht: |
Berlin ; Heidelberg
Springer
2010
|
| Schriftenreihe: | Intelligent systems reference library
2 |
| Schlagworte: | |
| Online-Zugang: | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=018800847&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| Beschreibung: | Literaturverz. S. 191 - 206 |
| Beschreibung: | XIV, 206 S. Ill., graph. Darst. 24 cm |
| ISBN: | 9783642047381 |
Internformat
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| 245 | 1 | 0 | |a Tree-structure based hybrid computational intelligence |b theoretical foundations and applications |c Yuehui Chen and Ajith Abraham |
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| 300 | |a XIV, 206 S. |b Ill., graph. Darst. |c 24 cm | ||
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| 490 | 1 | |a Intelligent systems reference library |v 2 | |
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Datensatz im Suchindex
| _version_ | 1819335792654286848 |
|---|---|
| adam_text | CONTENTS PART I: FOUNDATIONS OF COMPUTATIONAL INTELLIGENCE 1 FOUNDATIONS
OF COMPUTATIONAL INTELLIGENCE 3 1.1 INTRODUCTION 3 1.2 EVOLUTIONARY
ALGORITHMS 3 1.2.1 GENETIC PROGRAMMING 7 1.2.2 ESTIMATION OF
DISTRIBUTION ALGORITHM 11 1.2.3 POPULATION-BASED INCREMENTAL LEARNING 13
1.2.4 PROBABILISTIC INCREMENTAL PROGRAM EVOLUTION 14 1.3 SWARM
INTELLIGENCE 18 1.3.1 PARTICLE SWARM OPTIMIZATION 19 1.3.2 ANT COLONY
OPTIMIZATION 21 1.4 ARTIFICIAL NEURAL NETWORKS 23 1.4.1 ARCHITECTURE AND
LEARNING ALGORITHM 24 1.4.2 MULTILAYER PERCEPTRON 26 1.4.3
BACK-PROPAGATION ALGORITHM 27 1.4.4 EVOLUTIONARY ALGORITHM BASED
TRAINING 28 1.4.5 SELF ORGANIZING FEATURE MAPS 29 1.4.6 RADIAL BASIS
FUNCTION 30 1.4.7 RECURRENT NEURAL NETWORKS 30 1.4.8 ADAPTIVE RESONANCE
THEORY 31 1.5 FUZZY SYSTEMS 31 1.5.1 THE DEFINITION OF FUZZY SETS 32 1.6
TAKAGI-SUGENO FUZZY MODEL 32 1.6.1 UNIVERSAL APPROXIMATION PROPERTY 33
1.6.2 FUZZY EXPERT SYSTEMS - DESIGN CHALLENGES 34 1.7 PROBABILISTIC
COMPUTING 34 1.8 HYBRID INTELLIGENT SYSTEMS 35 1.9 MODELS OF HYBRID
INTELLIGENT SYSTEMS 36 BIBLIOGRAFISCHE INFORMATIONEN
HTTP://D-NB.INFO/996247416 DIGITALISIERT DURCH XII CONTENTS PART II:
FLEXIBLE NEURAL TREES 2 FLEXIBLE NEURAL TREE: FOUNDATIONS AND
APPLICATIONS 39 2.1 INTRODUCTION TO FLEXIBLE NEURAL TREE 39 2.2 FLEXIBLE
NEURAL TREE ALGORITHMS 40 2.2.1 ENCODING AND EVALUATION 40 2.2.2
FLEXIBLE NEURON INSTRUCTOR 40 2.2.3 FITNESS FUNCTION 42 2.2.4 STRUCTURE
AND PARAMETER LEARNING 42 2.2.5 FLEXIBLE NEURAL TREE APPLICATIONS 44
2.2.6 EXCHANGE RATE FORECASTING 64 2.2.7 FACE RECOGNITION 69 2.2.8
MICROARRAY-BASED CANCER CLASSIFICATION 73 2.2.9 PROTEIN FOLD RECOGNITION
76 2.3 MULTI INPUT MULTI OUTPUT FLEXIBLE NEURAL TREE 79 2.4
REPRESENTATION AND CALCULATION OF THE MIMO FNT 80 2.4.1 HYBRID ALGORITHM
FOR STRUCTURE AND PARAMETER LEARNING 82 2.4.2 HYBRID ALGORITHM FOR
FLEXIBLE NEURAL TREE MODEL ... 84 2.4.3 ILLUSTRATIVE EXAMPLES 84 2.5
ENSEMBLE OF FLEXIBLE NEURAL TREE 89 2.5.1 THE BASIC ENSEMBLE METHOD 90
2.5.2 THE GENERALIZED ENSEMBLE METHOD 90 2.5.3 THE LWPR METHOD 90 2.5.4
STOCK INDEX FORECASTING PROBLEM 91 2.6 STOCK INDEX FORECASTING
EXPERIMENTAL ILLUSTRATIONS 93 PART III: HIERARCHICAL NEURAL NETWORKS 3
HIERARCHICAL NEURAL NETWORKS 99 3.1 HIERARCHICAL RADIAL BASIS FUNCTION
NEURAL NETWORKS 99 3.1.1 THE RADIAL BASIS FUNCTION NETWORK 100 3.1.2
AUTOMATIC DESIGN OF HIERARCHICAL RADIAL BASIS FUNCTION NETWORK 101 3.1.3
TREE STRUCTURE OPTIMIZATION BY EXTENDED COMPACT GENETI CONTENTS XIII 3.2
HIERARCHICAL B-SPLINE NEURAL NETWORKS 108 3.2.1 THE B-SPLINE NETWORK 108
3.3 AUTOMATIC DESIGN OF HB-SPLINE NETWORK 109 3.3.1 ENCODE AND
CALCULATION FOR HB-SPLINE 109 3.3.2 TREE STRUCTURE AND PARAMETER
OPTIMIZATION 110 3.3.3 PROCEDURE OF THE GENERAL LEARNING ALGORITHM ILL
3.3.4 VARIABLE SELECTION IN THE HIERARCHICAL B-SPLINE NETWORK PARADIGMS
ILL 3.3.5 EXPERIMENTAL ILLUSTRATIONS ILL 3.3.6 WISCONSIN BREAST CANCER
DETECTION ILL 3.3.7 TIME-SERIES FORECASTING 113 3.4 HIERARCHICAL WAVELET
NEURAL NETWORKS 118 3.4.1 WAVELET NEURAL NETWORK 118 3.5 AUTOMATIC
DESIGN OF HIERARCHICAL WAVELET NEURAL NETWORK 119 3.5.1 ANT PROGRAMMING
FOR EVOLVING THE ARCHITECTURE OF HWNN 119 3.5.2 PARAMETER OPTIMIZATION
USING DIFFERENTIAL EVOLUTION ALGORITHM 121 3.5.3 PROCEDURE OF THE
GENERAL LEARNING ALGORITHM FOR HWNN 121 3.5.4 VARIABLE SELECTION USING
HWNN PARADIGMS 122 3.5.5 EXPERIMENTAL ILLUSTRATIONS 122 3.5.6
APPLICATION TO JENKINS-BOX TIME-SERIES 124 PART IV: HIERARCHICAL FUZZY
SYSTEMS 4 HIERARCHICAL FUZZY SYSTEMS 129 4.1 INTRODUCTION 129 4.2
TAKAGI-SUGENO FUZZY INFERENCE SYSTEM (TS-FS) 131 4.3 HIERARCHICAL TS-FS:
ENCODING AND EVALUATION 131 4.3.1 ENCODING 132 4.3.2 EVALUATION 133
4.3.3 OBJECTIVE FUNCTION 134 4.4 EVOLUTIONARY DESIGN OF HIERARCHICAL
TS-FS 135 4.4.1 ALGORITHM FOR DESIGNING HIERARCHICAL TS-F XIV CONTENTS
PART V: REVERSE ENGINEERING OF DYNAMICAL SYSTEMS 5 REVERSE ENGINEERING
OF DYNAMIC SYSTEMS 151 5.1 INTRODUCTION 151 5.2 CALCULATION AND
REPRESENTATION OF ADDITIVE MODELS 152 5.3 HYBRID ALGORITHM 153 5.3.1
TREE-STRUCTURE BASED EVOLUTIONARY ALGORITHM 153 5.3.2 EVOLVING AN
OPTIMAL OR NEAR-OPTIMAL STRUCTURE OF ADDITIVE MODEL 154 5.3.3 PARAMETER
OPTIMIZATION 156 5.3.4 SUMMARY OF GENERAL LEARNING ALGORITHM 158 5.3.5
EXPERIMENTAL ILLUSTRATIONS 159 5.3.6 DISCUSSIONS 165 5.4 INFERRING A
SYSTEM OF DIFFERENTIAL EQUATIONS 168 5.5 INFERENCE OF DIFFERENTIAL
EQUATION MODELS BY MULTI EXPRESSION PROGRAMMING 169 5.5.1 STRUCTURE
OPTIMIZATION BY THE MEP 169 5.5.2 PARAMETER OPTIMIZATION BY PARTICLE
SWARM OPTIMIZATION ALGORITHM 170 5.5.3 FITNESS DEFINITION 171 5.5.4
SUMMARY OF ALGORITHM 172 5.6 MODELING CHEMICAL REACTIONS 172 5.6.1
SIMPLE CHEMICAL REACTION MODEL 173 5.6.2 TWO-SPECIES LOTKA-VOLTERRA
MODEL 174 5.6.3 BIMOLECULAR REACTION 175 5.7 INFERRING GENE REGULATORY
NETWORKS 176 5.7.1 THE SMALL ARTIFICIAL GENE REGULATORY NETWORK 178
5.7.2 THE LARGE-SCALE ARTIFICIAL GENE REGULATORY NETWORK WITH NOISY
ENVIRONMENT 181 PART VI: CONCLUSIONS AND FUTURE RESEARCH 6 CONCLUDING
REMARKS AND FURTHER RESEARCH 185 6.1 LIMITATIONS OF CONVENTIONAL
COMPUTATIONAL INTELLIGENCE .... 185 6.2 TOWARDS TREE-STRUCTURE BASED
HIERARCHICAL HYBRID COMPUTATIONA
|
| any_adam_object | 1 |
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| dewey-ones | 006 - Special computer methods |
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| dewey-search | 006.3 |
| dewey-sort | 16.3 |
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| id | DE-604.BV035943652 |
| illustrated | Illustrated |
| indexdate | 2024-12-20T14:03:15Z |
| institution | BVB |
| isbn | 9783642047381 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-018800847 |
| oclc_num | 449852743 |
| open_access_boolean | |
| owner | DE-473 DE-BY-UBG |
| owner_facet | DE-473 DE-BY-UBG |
| physical | XIV, 206 S. Ill., graph. Darst. 24 cm |
| publishDate | 2010 |
| publishDateSearch | 2010 |
| publishDateSort | 2010 |
| publisher | Springer |
| record_format | marc |
| series | Intelligent systems reference library |
| series2 | Intelligent systems reference library |
| spellingShingle | Chen, Yuehui 1964- Abraham, Ajith 1968- Tree-structure based hybrid computational intelligence theoretical foundations and applications Intelligent systems reference library Computational intelligence Neuronales Netz (DE-588)4226127-2 gnd Soft Computing (DE-588)4455833-8 gnd Entscheidungsbaum (DE-588)4347788-4 gnd |
| subject_GND | (DE-588)4226127-2 (DE-588)4455833-8 (DE-588)4347788-4 |
| title | Tree-structure based hybrid computational intelligence theoretical foundations and applications |
| title_auth | Tree-structure based hybrid computational intelligence theoretical foundations and applications |
| title_exact_search | Tree-structure based hybrid computational intelligence theoretical foundations and applications |
| title_full | Tree-structure based hybrid computational intelligence theoretical foundations and applications Yuehui Chen and Ajith Abraham |
| title_fullStr | Tree-structure based hybrid computational intelligence theoretical foundations and applications Yuehui Chen and Ajith Abraham |
| title_full_unstemmed | Tree-structure based hybrid computational intelligence theoretical foundations and applications Yuehui Chen and Ajith Abraham |
| title_short | Tree-structure based hybrid computational intelligence |
| title_sort | tree structure based hybrid computational intelligence theoretical foundations and applications |
| title_sub | theoretical foundations and applications |
| topic | Computational intelligence Neuronales Netz (DE-588)4226127-2 gnd Soft Computing (DE-588)4455833-8 gnd Entscheidungsbaum (DE-588)4347788-4 gnd |
| topic_facet | Computational intelligence Neuronales Netz Soft Computing Entscheidungsbaum |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=018800847&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| volume_link | (DE-604)BV035704685 |
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