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Titlebook: Harmony Search Algorithm; Proceedings of the 3 Javier Del Ser Conference proceedings 2017 Springer Nature Singapore Pte Ltd. 2017 Evolution

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書(shū)目名稱(chēng)Harmony Search Algorithm
副標(biāo)題Proceedings of the 3
編輯Javier Del Ser
視頻videohttp://file.papertrans.cn/425/424332/424332.mp4
概述Offers a up-to-date reference for the research community working on Harmony Search.Presents views from worldwide experts on evolution- and nature-inspired heuristics.Describes novel applications of Ha
叢書(shū)名稱(chēng)Advances in Intelligent Systems and Computing
圖書(shū)封面Titlebook: Harmony Search Algorithm; Proceedings of the 3 Javier Del Ser Conference proceedings 2017 Springer Nature Singapore Pte Ltd. 2017 Evolution
描述.This book presents state-of-the-art technical contributions based around one of the most successful evolutionary optimization algorithms published to date: Harmony Search. Contributions span from novel technical derivations of this algorithm to applications in the broad fields of civil engineering, energy, transportation & mobility and health, among many others and focus not only on its cross-domain applicability, but also on its core evolutionary operators, including elements inspired from other meta-heuristics.? ? ? ? ? ?.The global scientific community is witnessing an upsurge in groundbreaking, new advances in all areas of computational intelligence, with a particular flurry of research focusing on evolutionary computation and bio-inspired optimization. Observed processes in nature and sociology have provided the basis for innovative algorithmic developments aimed at leveraging the inherent capability to adapt characterized by various animals, including ants, fireflies, wolves and humans. However, it is the behavioral patterns observed in music composition that motivated the advent of the Harmony Search algorithm, a meta-heuristic optimization algorithm that over the last deca
出版日期Conference proceedings 2017
關(guān)鍵詞Evolutionary Computation; Computational Intelligence; Soft Computing; Meta-heuristic Optimization; Harmo
版次1
doihttps://doi.org/10.1007/978-981-10-3728-3
isbn_softcover978-981-10-3727-6
isbn_ebook978-981-10-3728-3Series ISSN 2194-5357 Series E-ISSN 2194-5365
issn_series 2194-5357
copyrightSpringer Nature Singapore Pte Ltd. 2017
The information of publication is updating

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A Novel Grouping Harmony Search Algorithm for Clustering Problems number of clusters by means of the tailored design of the HS operators, which estimates this important structural clustering parameter as an implicit byproduct of the instance-to-cluster mapping performed by the algorithm. Apart from inferring the optimal number of clusters, simulation results veri
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Conference proceedings 2017inherent capability to adapt characterized by various animals, including ants, fireflies, wolves and humans. However, it is the behavioral patterns observed in music composition that motivated the advent of the Harmony Search algorithm, a meta-heuristic optimization algorithm that over the last deca
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the path toward the agreed fixed timeline. Due to the diversity and volatility of the SSA environment, each nation must address a unique set of needs while also contending with unforeseeable occurrences that might dramatically change their path to attaining sustainable development by a specific dat
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