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Sine cosine algorithm for optimization

Record Type:	Electronic resources : Monograph/item
Title/Author:	Sine cosine algorithm for optimizationby Jagdish Chand Bansal ... [et al.].
other author:	Bansal, Jagdish Chand.
Published:	Singapore :Springer Nature Singapore :2023.
Description:	x, 108 p. :ill. (chiefly color), digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Metaheuristics.
Online resource:	https://doi.org/10.1007/978-981-19-9722-8
ISBN:	9789811997228$q(electronic bk.)

Sine cosine algorithm for optimization
Sine cosine algorithm for optimization[electronic resource] /by Jagdish Chand Bansal ... [et al.]. - Singapore :Springer Nature Singapore :2023. - x, 108 p. :ill. (chiefly color), digital ;24 cm. - SpringerBriefs in applied sciences and technology. Computational intelligence. - SpringerBriefs in applied sciences and technology.Computational intelligence..

Introduction -- Sine Cosine Algorithm -- Sine Cosine Algorithm for Multi-Objective Optimization -- Sine Cosine Algorithm for Discrete Optimization Problems -- Advancements in the Sine Cosine Algorithm -- Conclusion and Further Research Directions.

Open access.

This open access book serves as a compact source of information on sine cosine algorithm (SCA) and a foundation for developing and advancing SCA and its applications. SCA is an easy, user-friendly, and strong candidate in the field of metaheuristics algorithms. Despite being a relatively new metaheuristic algorithm, it has achieved widespread acceptance among researchers due to its easy implementation and robust optimization capabilities. Its effectiveness and advantages have been demonstrated in various applications ranging from machine learning, engineering design, and wireless sensor network to environmental modeling. The book provides a comprehensive account of the SCA, including details of the underlying ideas, the modified versions, various applications, and a working MATLAB code for the basic SCA.

ISBN: 9789811997228$q(electronic bk.)

Standard No.: 10.1007/978-981-19-9722-8doiSubjects--Topical Terms:

757062
Metaheuristics.

LC Class. No.: QA76.9.A43

Dewey Class. No.: 005.13

Sine cosine algorithm for optimization
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245 0 0 $a Sine cosine algorithm for optimization $h [electronic resource] / $c by Jagdish Chand Bansal ... [et al.].
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300 $a x, 108 p. : $b ill. (chiefly color), digital ; $c 24 cm.
490 1 $a SpringerBriefs in applied sciences and technology. Computational intelligence
505 0 $a Introduction -- Sine Cosine Algorithm -- Sine Cosine Algorithm for Multi-Objective Optimization -- Sine Cosine Algorithm for Discrete Optimization Problems -- Advancements in the Sine Cosine Algorithm -- Conclusion and Further Research Directions.
506 $a Open access.
520 $a This open access book serves as a compact source of information on sine cosine algorithm (SCA) and a foundation for developing and advancing SCA and its applications. SCA is an easy, user-friendly, and strong candidate in the field of metaheuristics algorithms. Despite being a relatively new metaheuristic algorithm, it has achieved widespread acceptance among researchers due to its easy implementation and robust optimization capabilities. Its effectiveness and advantages have been demonstrated in various applications ranging from machine learning, engineering design, and wireless sensor network to environmental modeling. The book provides a comprehensive account of the SCA, including details of the underlying ideas, the modified versions, various applications, and a working MATLAB code for the basic SCA.
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650 0 $a Computer programming. $3 181992
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650 2 4 $a Optimization. $3 274084
650 2 4 $a Algorithms. $3 184661
700 1 $a Bansal, Jagdish Chand. $3 830175
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