http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
XIV, 201 p. 60 illus., 11 illus. in color. online resource.
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. .
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.
edited by Satchidananda Dehuri, Alok Kumar Jagadev, Mrutyunjaya Panda.
Artificial Intelligence (incl. Robotics)
Studies in Computational Intelligence, 592