Multi-objective swarm intelligent systems: theory & experiences
Gespeichert in:
| Weitere Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Berlin [u.a.]
Springer
2010
|
| Schriftenreihe: | Studies in computational intelligence
261 |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | XXI, 207 S. Ill., graph. Darst., Kt. |
| ISBN: | 9783642051647 |
Internformat
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Datensatz im Suchindex
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|---|---|
| adam_text | CONTENTS MULTIOBJECTIVE GAUSSIAN PARTICLE SWARM APPROACH APPLIED TO
MULTI-LOOP PI CONTROLLER TUNING OF A QUADRUPLE-TANK SYSTEM 1 LEANDRO DOS
SANTOS COELHO, HELON VICENTE HULTMANN AY ALA, NADIA NEDJAH, LUIZA DE
MACEDO MOURELLE 1.1 INTRODUCTION 2 1.2 DESCRIPTION OF QUADRUPLE-TANK
PROCESS 3 1.3 FUNDAMENTALS OF MULTI-OBJECTIVE OPTIMIZATION AND PSO ....
5 1.3.1 MULTI-OBJECTIVE OPTIMIZATION 6 1.3.2 CLASSICAL PSO AND MOPSO
APPROACHES 7 1.3.3 THE PROPOSED MGPSO APPROACH 9 1.4 SIMULATION RESULTS
9 1.5 SUMMARY 14 REFERENCES 14 A NON-ORDERED RULE INDUCTION ALGORITHM
THROUGH MULTI-OBJECTIVE PARTICLE SWARM OPTIMIZATION: ISSUES AND
APPLICATIONS 17 ANDRE B. DE CARVALHO, AURORA POZO, SILVIA VERGUIO 2.1
INTRODUCTION 17 2.2 RULE LEARNING CONCEPTS 20 2.3 PERFORMANCE ASSESSMENT
OF STOCHASTIC MULTI-OBJECTIVE OPTIMIZERS 23 2.3.1 PERFORMANCE ASSESSMENT
26 2.4 MULTI-OBJECTIVE PARTICLE SWARM OPTIMIZATION 27 2.5 RULE LEARNING
WITH MOPSO 29 2.6 MOPSO EVALUATION 31 2.6.1 AUC COMPARISON 32 2.6.2
PARETO FRONT ANALYSIS 33 BIBLIOGRAFISCHE INFORMATIONEN
HTTP://D-NB.INFO/997432438 DIGITALISIERT DURCH X CONTENTS 2.7 PREDICTING
FAULTS 35 2.7.1 DATASET 36 2.7.2 EVALUATION MEASURES 36 2.7.3 ALGORITHMS
37 2.7.4 AUC COMPARISON 37 2.7.5 INFLUENCE OF C-K SUITE METRICS IN
FAULT-PRONENESS ... 37 2.8 RELATED WORKS 39 2.9 CONCLUSIONS 40
REFERENCES 41 3 USE OF MULTIOBJECTIVE EVOLUTIONARY ALGORITHMS IN WATER
RESOURCES ENGINEERING 45 FRANCISCO VEMCIUS FERNANDES BARROS, EDUARDO
SAVIO PASSOS RODRIGUES MARTINS, LUIZ SERGIO VASCONCELOS NASCIMENTO,
DIRCEU SILVEIRA REIS JR. 3.1 INTRODUCTION 45 3.2 LITERATURE REVIEW 47
3.3 EVOLUTIONARY ALGORITHM 48 3.3.1 UNI-OBJECTIVE OPTIMIZATION 49 3.3.2
MULTIOBJECTIVE APPROACH USING PARETO DOMINANCE CRITERION 54 3.4
EVALUATION OF THE ALGORITHMS WITH TEST FUNCTIONS 58 3.4.1 TEST FUNCTIONS
AND THEIRS THEORETICAL MINIMA 58 3.5 USE OF MULTIOBJECTIVE EVOLUTIONARY
ALGORITHMS IN CALIBRATION OF HYDROLOGIE MODELS 62 3.5.1 HYDROLOGIE MODEL
63 3.5.2 DISCUSSION OF THE RESULTS 66 3.6 USE OF MULTIOBJECTIVE
EVOLUTIONARY ALGORITHMS IN RESERVOIRS SYSTEM OPERATION 71 3.6.1
BACKGROUND 71 3.6.2 THE RESERVOIR SYSTEM 72 3.6.3 THE CURRENT OPERATING
POLICY 74 3.6.4 DERIVATION OF A NEW OPERATING POLICY 75 3.7 SUMMARY 78
REFERENCES 80 4 MICRO-MOPSO: A MULTI-OBJECTIVE PARTICLE SWARM OPTIMIZER
THAT USES A VERY SMALL POPULATION SIZE 83 JUAN CONTENTS XI 4.5.2
REINITIALIZATION PROCESS 92 4.5.3 MUTATION OPERATOR 92 4.6 EXPERIMENTS
AND RESULTS 93 4.6.1 PERFORMANCE MEASURES 93 4.6.2 EXPERIMENTS 97 4.6.3
RESULTS 98 4.7 CONCLUSIONS AND FUTURE WORK 100 REFERENCES 101 DYNAMIC
MULTI-OBJECTIVE OPTIMISATION USING PSO 105 MARDE GREEFF, ANDRIES P.
ENGELBRECHT 5.1 INTRODUCTION 105 5.2 BACKGROUND 107 5.3 VECTOR EVALUATED
PARTICLE SWARM OPTIMISATION 109 5.3.1 VEPSO FOR DYNAMIC MULTI-OBJECTIVE
OPTIMISATION 110 5.4 EXPERIMENTS 110 5.4.1 BENCHMARK FUNCTIONS ILL 5.4.2
PERFORMANCE METRICS 112 5.4.3 STATISTICAL ANALYSIS 113 5.5 RESULTS 114
5.5.1 OVERALL PERFORMANCE 114 5.5.2 POPULATION SIZE 117 5.5.3 RESPONSE
STRATEGIES 120 5.6 SUMMARY 121 REFERENCES 121 META-PSO FOR
MULTI-OBJECTIVE EM PROBLEMS 125 MARCO MUSSETTA, PAOLA PIRINOLI, STEFANO
SELLERI, RICCARDO E. ZIEH 6.1 INTRODUCTION 125 6.2 BASIC PSO ALGORITHM
130 6.3 UNDIFFERENTIATED META-PSO 132 6.3.1 META-PSO 132 6.3.2 MODIFIED
META-PSO 133 6.3.3 STABILIZED MODIFIED META-PSO 134 6.4 DIFFERENTIATED
META-PSO ALGORITHMS 134 6.4.1 ABSOLUTE LEADER META-PSO 134 6.4.2
DEMOCRATIC LEADER META-PSO 135 6.5 ALGORITHM TUNING 136 6.6 META-PSO FOR
MULTI-OBJECTIVE OPTIMIZATION 139 6. XII CONTENTS 7 MULTI-OBJECTIVE
WAVELET-BASED PIXEL-LEVEL IMAGE FUSION USING MULTI-OBJECTIVE
CONSTRICTION PARTICLE SWARM OPTIMIZATION 151 YIFENG NIU, LINCHENG SHEN,
XIAOHUA HUO, GUANGXIA LIANG 7.1 INTRODUCTION 152 7.2 FUNDAMENTALS OF
WAVELET TRANSFORM 153 7.2.1 WAVELET TRANSFORM OF 1-D SIGNALS 154 7.2.2
WAVELET TRANSFORM OF 2-D IMAGES 155 7.3 MULTI-OBJECTIVE PIXEL-LEVEL
IMAGE FUSION BASED ON DISCRETE WAVELET TRANSFORM 157 7.4 EVALUATION
METRICS OF IMAGE FUSION 158 7.4.1 IMAGE FEATURE METRICS 159 7.4.2 IMAGE
SIMILARITY METRICS 159 7.4.3 MUTUAL INFORMATION METRICS 160 7.5 MOCPSO
ALGORITHM 162 7.5.1 MOCPSO FLOW 163 7.5.2 INITIALIZATION OF ALGORITHM
163 7.5.3 UPDATE PARTICLE SWARM 164 7.5.4 ADAPTIVE MUTATION 164 7.5.5
REPOSITORY CONTROL 165 7.5.6 UNIFORM DESIGN FOR PARAMETER ESTABLISHMENT
166 7.5.7 CONVERGENCE ANALYSIS OF MOCPSO 167 7.6 EXPERIMENTS AND
ANALYSIS 168 7.6.1 UNIFORM DESIGN FOR MOCPSO PARAMETERS 169 7.6.2
COMPARISON OF MOCPSO AND MOPSO 170 7.6.3 MULTI-FOCUS IMAGE FUSION 171
7.6.4 BLIND IMAGE FUSION 173 7.6.5 MULTI-RESOLUTION IMAGE FUSION 173
7.6.6 COLOR IMAGE FUSION 175 7.7 CONCLUSIONS 176 REFERENCES 177 8
MULTI-OBJECTIVE DAMAGE IDENTIFICATION USING PARTICLE SWARM OPTIMIZATION
TECHNIQUES 179 RICARDO PERERA, SHENG-EN FANG 8. CONTENTS XIII 8.5.3
SELECTION OF PBEST AND GBEST 189 8.5.4 USE OF A MUTATION OPERATOR 190
8.6 BENCHMARKING EXPERIMENTS 191 8.6.1 SIMPLY SUPPORTED BEAM 192 8.6.2
EXPERIMENTAL REINFORCED CONCRETE FRAME 199 8.7 CONCLUSIONS 205
REFERENCES 205 AUTHOR INDEX 209 INDEX 211
|
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| dewey-sort | 16.3 |
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| discipline | Informatik Mathematik |
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| spelling | Multi-objective swarm intelligent systems theory & experiences Nadia Nedjah ... (eds.) Berlin [u.a.] Springer 2010 XXI, 207 S. Ill., graph. Darst., Kt. txt rdacontent n rdamedia nc rdacarrier Studies in computational intelligence 261 Mehrkriterielle Optimierung (DE-588)4610682-0 gnd rswk-swf Schwarmintelligenz (DE-588)4793676-9 gnd rswk-swf (DE-588)4143413-4 Aufsatzsammlung gnd-content Schwarmintelligenz (DE-588)4793676-9 s Mehrkriterielle Optimierung (DE-588)4610682-0 s DE-604 Nedjah, Nadia edt Studies in computational intelligence 261 (DE-604)BV020822171 261 DNB Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=018703765&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Multi-objective swarm intelligent systems theory & experiences Studies in computational intelligence Mehrkriterielle Optimierung (DE-588)4610682-0 gnd Schwarmintelligenz (DE-588)4793676-9 gnd |
| subject_GND | (DE-588)4610682-0 (DE-588)4793676-9 (DE-588)4143413-4 |
| title | Multi-objective swarm intelligent systems theory & experiences |
| title_auth | Multi-objective swarm intelligent systems theory & experiences |
| title_exact_search | Multi-objective swarm intelligent systems theory & experiences |
| title_full | Multi-objective swarm intelligent systems theory & experiences Nadia Nedjah ... (eds.) |
| title_fullStr | Multi-objective swarm intelligent systems theory & experiences Nadia Nedjah ... (eds.) |
| title_full_unstemmed | Multi-objective swarm intelligent systems theory & experiences Nadia Nedjah ... (eds.) |
| title_short | Multi-objective swarm intelligent systems |
| title_sort | multi objective swarm intelligent systems theory experiences |
| title_sub | theory & experiences |
| topic | Mehrkriterielle Optimierung (DE-588)4610682-0 gnd Schwarmintelligenz (DE-588)4793676-9 gnd |
| topic_facet | Mehrkriterielle Optimierung Schwarmintelligenz Aufsatzsammlung |
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