Product Description
Swarm Intelligence: Principles Advances and Applications delivers in-depth coverage of bat artificial fish swarm firefly cuckoo search flower pollination artificial bee colony wolf search and gray wolf optimization algorithms. The book begins with a brief introduction to mathematical optimization addressing basic concepts related to swarm intelligence such as randomness random walks and chaos theory. The text then:Describes the various swarm intelligence optimization methods standardizing the variants hybridizations and algorithms whenever possibleDiscusses variants that focus more on binary discrete constrained adaptive and chaotic versions of the swarm optimizersDepicts real-world applications of the individual optimizers emphasizing variable selection and fitness function designDetails the similarities differences weaknesses and strengths of each swarm optimization methodDraws parallels between the operators and searching manners of the different algorithmsSwarm Intelligence: Principles Advances and Applications presents a comprehensive treatment of modern swarm intelligence optimization methods complete with illustrative examples and an extendable MATLAB® package for feature selection in wrapper mode applied on different data sets with benchmarking using different evaluation criteria. The book provides beginners with a solid foundation of swarm intelligence fundamentals and offers experts valuable insight into new directions and hybridizations. | Swarm Intelligence Principles Advances and Applications
Crc Press Swarm Intelligence Principles Advances And Applications 09780367737542
Swarm Intelligence: Principles Advances and Applications delivers in-depth coverage of bat artificial fish swarm firefly cuckoo search flower pollination artificial bee colony wolf search and gray wolf optimization algorithms. The book begins with a brief introduction to mathematical optimization addressing basic concepts related to swarm intelligence such as randomness random walks and chaos theory. The text then:Describes the various swarm intelligence optimization methods standardizing the variants hybridizations and algorithms whenever possibleDiscusses variants that focus more on binary discrete constrained adaptive and chaotic versions of the swarm optimizersDepicts real-world applications of the individual optimizers emphasizing variable selection and fitness function designDetails the similarities differences weaknesses and strengths of each swarm optimization methodDraws parallels between the operators and searching manners of the different algorithmsSwarm Intelligence: Principles Advances and Applications presents a comprehensive treatment of modern swarm intelligence optimization methods complete with illustrative examples and an extendable MATLAB® package for feature selection in wrapper mode applied on different data sets with benchmarking using different evaluation criteria. The book provides beginners with a solid foundation of swarm intelligence fundamentals and offers experts valuable insight into new directions and hybridizations. | Swarm Intelligence Principles Advances and Applications
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