Metaheuristic optimization algorithms: optimizers, analysis, and applications
Front Cover -- Metaheuristic Optimization Algorithms -- Copyright Page -- Contents -- List of contributors -- 1 Particle swarm optimization algorithm: review and applications -- 1.1 Introduction -- 1.2 Particle swarm optimization -- 1.2.1 Standard particle swarm optimization -- 1.2.2 Particle swarm...
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Weitere Verfasser: | |
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Format: | Elektronisch E-Book |
Sprache: | English |
Veröffentlicht: |
Cambridge
Elsevier
2024
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Online-Zugang: | DE-706 Volltext |
Zusammenfassung: | Front Cover -- Metaheuristic Optimization Algorithms -- Copyright Page -- Contents -- List of contributors -- 1 Particle swarm optimization algorithm: review and applications -- 1.1 Introduction -- 1.2 Particle swarm optimization -- 1.2.1 Standard particle swarm optimization -- 1.2.2 Particle swarm optimization algorithm -- 1.3 Related works -- 1.3.1 Neural networks -- 1.3.2 Feature selection -- 1.3.3 Data clustering -- 1.3.4 Mobile robots -- 1.4 Discussion -- 1.5 Conclusion -- References -- 2 Social spider optimization algorithm: survey and new applications -- 2.1 Introduction -- 2.2 Related work -- 2.2.1 Medical field -- 2.2.2 Engineering field -- 2.2.3 Mathematics field -- 2.2.4 Artificial intelligence field -- 2.2.5 Data science -- 2.3 Social spider optimization method -- 2.4 Experiment result -- 2.5 Discussion -- 2.6 Conclusion -- References -- 3 Animal migration optimization algorithm: novel optimizer, analysis, and applications -- 3.1 Introduction -- 3.2 Animal migration optimization algorithm procedure -- 3.3 Related works -- 3.3.1 Image processing -- 3.3.2 Data clustering -- 3.3.3 Data mining -- 3.3.4 Benchmark functions -- 3.3.5 Computer networks -- 3.3.6 Neural networks -- 3.3.7 Other applications -- 3.4 Discussion -- 3.5 Conclusion -- References -- 4 A Survey of cuckoo search algorithm: optimizer and new applications -- 4.1 Introduction -- 4.2 Cuckoo search algorithm -- 4.2.1 Cuckoo rearing conduct -- 4.2.2 Lévy trips in nature -- 4.3 Related works -- 4.4 Method -- 4.5 Discussion -- 4.6 Advanced work -- 4.7 Conclusion -- References -- 5 Teaching-learning-based optimization algorithm: analysis study and its application -- 5.1 Introduction -- 5.2 Teaching-learning-based optimization -- 5.2.1 Teacher section -- 5.2.2 Learner section -- 5.3 Literature review -- 5.3.1 Optimization problem -- 5.3.2 Technoeconomic analysis. |
Beschreibung: | 1 Online-Ressource (291 Seiten) |
ISBN: | 9780443139253 |
DOI: | 10.1016/C2022-0-02901-9 |
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520 | 3 | |a Front Cover -- Metaheuristic Optimization Algorithms -- Copyright Page -- Contents -- List of contributors -- 1 Particle swarm optimization algorithm: review and applications -- 1.1 Introduction -- 1.2 Particle swarm optimization -- 1.2.1 Standard particle swarm optimization -- 1.2.2 Particle swarm optimization algorithm -- 1.3 Related works -- 1.3.1 Neural networks -- 1.3.2 Feature selection -- 1.3.3 Data clustering -- 1.3.4 Mobile robots -- 1.4 Discussion -- 1.5 Conclusion -- References -- 2 Social spider optimization algorithm: survey and new applications -- 2.1 Introduction -- 2.2 Related work -- 2.2.1 Medical field -- 2.2.2 Engineering field -- 2.2.3 Mathematics field -- 2.2.4 Artificial intelligence field -- 2.2.5 Data science -- 2.3 Social spider optimization method -- 2.4 Experiment result -- 2.5 Discussion -- 2.6 Conclusion -- References -- 3 Animal migration optimization algorithm: novel optimizer, analysis, and applications -- 3.1 Introduction -- 3.2 Animal migration optimization algorithm procedure -- 3.3 Related works -- 3.3.1 Image processing -- 3.3.2 Data clustering -- 3.3.3 Data mining -- 3.3.4 Benchmark functions -- 3.3.5 Computer networks -- 3.3.6 Neural networks -- 3.3.7 Other applications -- 3.4 Discussion -- 3.5 Conclusion -- References -- 4 A Survey of cuckoo search algorithm: optimizer and new applications -- 4.1 Introduction -- 4.2 Cuckoo search algorithm -- 4.2.1 Cuckoo rearing conduct -- 4.2.2 Lévy trips in nature -- 4.3 Related works -- 4.4 Method -- 4.5 Discussion -- 4.6 Advanced work -- 4.7 Conclusion -- References -- 5 Teaching-learning-based optimization algorithm: analysis study and its application -- 5.1 Introduction -- 5.2 Teaching-learning-based optimization -- 5.2.1 Teacher section -- 5.2.2 Learner section -- 5.3 Literature review -- 5.3.1 Optimization problem -- 5.3.2 Technoeconomic analysis. | |
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spelling | Metaheuristic optimization algorithms optimizers, analysis, and applications edited by Laith Abualigah Cambridge Elsevier 2024 1 Online-Ressource (291 Seiten) txt rdacontent c rdamedia cr rdacarrier Front Cover -- Metaheuristic Optimization Algorithms -- Copyright Page -- Contents -- List of contributors -- 1 Particle swarm optimization algorithm: review and applications -- 1.1 Introduction -- 1.2 Particle swarm optimization -- 1.2.1 Standard particle swarm optimization -- 1.2.2 Particle swarm optimization algorithm -- 1.3 Related works -- 1.3.1 Neural networks -- 1.3.2 Feature selection -- 1.3.3 Data clustering -- 1.3.4 Mobile robots -- 1.4 Discussion -- 1.5 Conclusion -- References -- 2 Social spider optimization algorithm: survey and new applications -- 2.1 Introduction -- 2.2 Related work -- 2.2.1 Medical field -- 2.2.2 Engineering field -- 2.2.3 Mathematics field -- 2.2.4 Artificial intelligence field -- 2.2.5 Data science -- 2.3 Social spider optimization method -- 2.4 Experiment result -- 2.5 Discussion -- 2.6 Conclusion -- References -- 3 Animal migration optimization algorithm: novel optimizer, analysis, and applications -- 3.1 Introduction -- 3.2 Animal migration optimization algorithm procedure -- 3.3 Related works -- 3.3.1 Image processing -- 3.3.2 Data clustering -- 3.3.3 Data mining -- 3.3.4 Benchmark functions -- 3.3.5 Computer networks -- 3.3.6 Neural networks -- 3.3.7 Other applications -- 3.4 Discussion -- 3.5 Conclusion -- References -- 4 A Survey of cuckoo search algorithm: optimizer and new applications -- 4.1 Introduction -- 4.2 Cuckoo search algorithm -- 4.2.1 Cuckoo rearing conduct -- 4.2.2 Lévy trips in nature -- 4.3 Related works -- 4.4 Method -- 4.5 Discussion -- 4.6 Advanced work -- 4.7 Conclusion -- References -- 5 Teaching-learning-based optimization algorithm: analysis study and its application -- 5.1 Introduction -- 5.2 Teaching-learning-based optimization -- 5.2.1 Teacher section -- 5.2.2 Learner section -- 5.3 Literature review -- 5.3.1 Optimization problem -- 5.3.2 Technoeconomic analysis. Abualigah, Laith Mohammad Qasim (DE-588)1176162497 edt Erscheint auch als Druck-Ausgabe 9780443139253 https://doi.org/10.1016/C2022-0-02901-9 Verlag URL des Erstveröffentlichers Volltext |
spellingShingle | Metaheuristic optimization algorithms optimizers, analysis, and applications |
title | Metaheuristic optimization algorithms optimizers, analysis, and applications |
title_auth | Metaheuristic optimization algorithms optimizers, analysis, and applications |
title_exact_search | Metaheuristic optimization algorithms optimizers, analysis, and applications |
title_full | Metaheuristic optimization algorithms optimizers, analysis, and applications edited by Laith Abualigah |
title_fullStr | Metaheuristic optimization algorithms optimizers, analysis, and applications edited by Laith Abualigah |
title_full_unstemmed | Metaheuristic optimization algorithms optimizers, analysis, and applications edited by Laith Abualigah |
title_short | Metaheuristic optimization algorithms |
title_sort | metaheuristic optimization algorithms optimizers analysis and applications |
title_sub | optimizers, analysis, and applications |
url | https://doi.org/10.1016/C2022-0-02901-9 |
work_keys_str_mv | AT abualigahlaithmohammadqasim metaheuristicoptimizationalgorithmsoptimizersanalysisandapplications |