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[null,"1.","Record Nr.",null,"UNINA9910299695903321"]
[null,null,"Titolo",null,"Multi-objective Swarm Intelligence : Theoretical Advances and Applications / / edited by Satchidananda Dehuri, Alok Kumar Jagadev, Mrutyunjaya Panda"]
[null,null,"Pubbl/distr/stampa",null,"Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2015"]
[null,null,"ISBN",null,"9783662463093"]
[{"$nulls":4},"3662463091"]
[null,null,"Edizione",null,"[1st ed. 2015.]"]
[null,null,"Descrizione fisica",null,"1 online resource (XIV, 201 p. 60 illus., 11 illus. in color.)"]
[null,null,"Collana",null,"Studies in Computational Intelligence, , 1860-949X ; ; 592"]
[null,null,"Disciplina",null,"006.3824"]
[null,null,"Soggetti",null,"Computational intelligence"]
[{"$nulls":4},"Artificial intelligence"]
[{"$nulls":4},"Computational Intelligence"]
[{"$nulls":4},"Artificial Intelligence"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Bibliographic Level Mode of Issuance: Monograph"]
[null,null,null,"Nota di bibliografia","Includes bibliographical references."]
[null,null,"Nota di contenuto",null,"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."]
[null,null,null,"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.       ."]