Multi-objective Swarm Intelligence [[electronic resource] ] : Theoretical Advances and Applications / / edited by Satchidananda Dehuri, Alok Kumar Jagadev, Mrutyunjaya Panda
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| Titolo: |
Multi-objective Swarm Intelligence [[electronic resource] ] : Theoretical Advances and Applications / / edited by Satchidananda Dehuri, Alok Kumar Jagadev, Mrutyunjaya Panda
|
| Pubblicazione: | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2015 |
| Edizione: | 1st ed. 2015. |
| Descrizione fisica: | 1 online resource (XIV, 201 p. 60 illus., 11 illus. in color.) |
| Disciplina: | 006.3824 |
| Soggetto topico: | Computational intelligence |
| Artificial intelligence | |
| Computational Intelligence | |
| Artificial Intelligence | |
| Persona (resp. second.): | DehuriSatchidananda |
| JagadevAlok Kumar | |
| PandaMrutyunjaya | |
| Note generali: | Bibliographic Level Mode of Issuance: Monograph |
| Nota di bibliografia: | Includes bibliographical references. |
| Nota di contenuto: | Introduction -- Behavior of Bacterial Colony -- E.coli Bacterial Colonies -- Optimization based on E.coli Bacterial Colony -- Classification of BFO Algorithm -- Multi-objective optimization based on BF -- An overview of BFO Applications -- Conclusion. |
| Sommario/riassunto: | The aim of this book is to understand the state-of-the-art theoretical and practical advances of swarm intelligence. It comprises seven contemporary relevant chapters. In chapter 1, a review of Bacteria Foraging Optimization (BFO) techniques for both single and multiple criterions problem is presented. A survey on swarm intelligence for multiple and many objectives optimization is presented in chapter 2 along with a topical study on EEG signal analysis. Without compromising the extensive simulation study, a comparative study of variants of MOPSO is provided in chapter 3. Intractable problems like subset and job scheduling problems are discussed in chapters 4 and 7 by different hybrid swarm intelligence techniques. An attempt to study image enhancement by ant colony optimization is made in chapter 5. Finally, chapter 7 covers the aspect of uncertainty in data by hybrid PSO. . |
| Titolo autorizzato: | Multi-objective Swarm Intelligence |
| ISBN: | 3-662-46309-1 |
| Formato: | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione: | Inglese |
| Record Nr.: | 9910299695903321 |
| Lo trovi qui: | Univ. Federico II |
| Opac: | Controlla la disponibilità qui |
Serie:
Studies in Computational Intelligence, . 1860-949X ; ; 592