GSA-BBO Hybridization Algorithm - Rather, Sajad Ahmad
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In recent years, many heuristic optimization methods have been developed. Many of these methods are inspired by swarm behaviors' in nature. In this book, a new optimization algorithm based on newtons law of gravity and biogeography is introduced. In the proposed algorithm, the searching space of GSA is increased from local population range to global by using the concepts of biogeography. Also, the fitness of agents is optimized in GSA by using mathematical analysis.

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Produktbeschreibung
In recent years, many heuristic optimization methods have been developed. Many of these methods are inspired by swarm behaviors' in nature. In this book, a new optimization algorithm based on newtons law of gravity and biogeography is introduced. In the proposed algorithm, the searching space of GSA is increased from local population range to global by using the concepts of biogeography. Also, the fitness of agents is optimized in GSA by using mathematical analysis.
Autorenporträt
Er. Sajad Ahmad Rather is a Lecturer of Computer Science And Engineering at Government College Of Engineering And Technology (GCET), Safapora, Ganderbal, Kashmir. His Research Areas of interest are in Machine Learning, Artificial Intelligence, Image Processing, etc. He is the Associate Member of IEI and Life Member of ISTE.