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Titlebook: Applications of Bat Algorithm and its Variants; Nilanjan Dey,V. Rajinikanth Book 2021 The Editor(s) (if applicable) and The Author(s), und

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發(fā)表于 2025-3-21 18:34:12 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱(chēng)Applications of Bat Algorithm and its Variants
影響因子2023Nilanjan Dey,V. Rajinikanth
視頻videohttp://file.papertrans.cn/160/159306/159306.mp4
發(fā)行地址Discusses solutions to complicated optimization problems in several real-world applications.Highlights essential concepts in connection with the traditional bat algorithm and its variants.Serves as a
學(xué)科分類(lèi)Springer Tracts in Nature-Inspired Computing
圖書(shū)封面Titlebook: Applications of Bat Algorithm and its Variants; Nilanjan Dey,V. Rajinikanth Book 2021 The Editor(s) (if applicable) and The Author(s), und
影響因子.This book highlights essential concepts in connection with the traditional bat algorithm and its recent variants, as well as its application to find optimal solutions for a variety of real-world engineering and medical problems. Today, swarm intelligence-based meta-heuristic algorithms are extensively being used to address a wide range of real-world optimization problems due to their adaptability and robustness. Developed in 2009, the bat algorithm (BA) is one of the most successful swarm intelligence procedures, and has been used to tackle optimization tasks for more than a decade. The BA’s mathematical model is quite straightforward and easy to understand and enhance, compared to other swarm approaches. Hence, it has attracted the attention of researchers who are working to find optimal solutions in a diverse range of domains, such as N-dimensional numerical optimization, constrained/unconstrained optimization and linear/nonlinear optimization problems. Along with the traditional BA, its enhanced versions are now also being used to solve optimization problems in science, engineering and medical applications around the globe..
Pindex Book 2021
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https://doi.org/10.1007/978-3-322-93463-5the literature. The proposed algorithm and various t optimizers are applied over datasets obtained from the UCI repository. The results prove the ability of the proposed algorithm to search the feature space for optimal feature combinations.
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,Bat Algorithm with Applications to Signal, Speech, and Image Processing—A Review,e new variants and developments on BA applied for aforesaid applications. The detailed implementation of the algorithms and their objective functions is also presented in this chapter. Thus, the information provided in this chapter could help to move area forward.
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Die Struktur dieses Buches: Eine Einleitung, solution of multi-objective optimization problems, unlike single-objective problems, is a set of vectors rather than a single decision vector. In multi-objective optimization problems, especially if there are intricate objectives, the computational cost of the problem increases. In other words, whi
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Aufbereitung und Auswertung der Daten,ach and the performance of the considered BAs is validated by computing the essential image performance metrics (IPM), and the result of this study confirms that the final outcome attained with the BW-guided BA offered better result compared to the LF and IM-based techniques. This technique is teste
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