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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Er. Sajad Ahmad Rather é professor de Informática e Engenharia no Colégio Governamental de Engenharia e Tecnologia, Safapora, Ganderbal, Caxemira. As suas áreas de investigação de interesse são a aprendizagem de máquinas, Inteligência Artificial, Processamento de Imagem, etc. Publicou trabalhos de investigação em revistas de renome e apresentou trabalhos de investigação.
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Taschenbuch. Zustand: Neu. GSA-BBO Hybridization Algorithm | Improvement in GSA, based on Newtons Law of Gravitation Using BBO, Nature Inspired Algorithm | Sajad Ahmad Rather | Taschenbuch | 56 S. | Englisch | 2018 | LAP LAMBERT Academic Publishing | EAN 9786139844432 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. Artikel-Nr. 114109652
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