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Multi-objective Swarm Intelligence: Theoretical Advances and Applications (Studies in Computational Intelligence, Band 592) - Softcover

Buch 116 von 538: Studies in Computational Intelligence
 
9783662523650: Multi-objective Swarm Intelligence: Theoretical Advances and Applications (Studies in Computational Intelligence, Band 592)
Softcover
ISBN 10: 3662523655 ISBN 13: 9783662523650
Verlag: Springer, 2016

Inhaltsangabe

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.

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Von der hinteren Coverseite

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.

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Verlag
Springer
Erscheinungsdatum
2016
Sprache
Englisch
ISBN 10 
3662523655
ISBN 13 
9783662523650
Einband
Taschenbuch
Anzahl der Seiten
216
Herausgeber
Dehuri Satchidananda, Jagadev Alok Kumar, Panda Mrutyunjaya
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