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Metaheuristics for data clustering a...

Abraham, Ajith.

Metaheuristics for data clustering and image segmentation

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Metaheuristics for data clustering and image segmentationby Meera Ramadas, Ajith Abraham.
作者:	Ramadas, Meera.
其他作者:	Abraham, Ajith.
出版者:	Cham :Springer International Publishing :2019.
面頁冊數:	ix, 163 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
標題:	Metaheuristics.
電子資源:	https://doi.org/10.1007/978-3-030-04097-0
ISBN:	9783030040970$q(electronic bk.)

Metaheuristics for data clustering and image segmentation
Ramadas, Meera.

Metaheuristics for data clustering and image segmentation[electronic resource] /by Meera Ramadas, Ajith Abraham. - Cham :Springer International Publishing :2019. - ix, 163 p. :ill., digital ;24 cm. - Intelligent systems reference library,v.1521868-4394 ;. - Intelligent systems reference library ;v.24..

Introduction -- METAHEURISTICS AND DATA CLUSTERING -- REVISED MUTATION STRATEGY FOR DIFFERENTIAL EVOLUTION ALGORITHM -- SEARCH strategy Flower Pollination Algorithm with Differential Evolution.

In this book, differential evolution and its modified variants are applied to the clustering of data and images. Metaheuristics have emerged as potential algorithms for dealing with complex optimization problems, which are otherwise difficult to solve using traditional methods. In this regard, differential evolution is considered to be a highly promising technique for optimization and is being used to solve various real-time problems. The book studies the algorithms in detail, tests them on a range of test images, and carefully analyzes their performance. Accordingly, it offers a valuable reference guide for all researchers, students and practitioners working in the fields of artificial intelligence, optimization and data analytics.

ISBN: 9783030040970$q(electronic bk.)

Standard No.: 10.1007/978-3-030-04097-0doiSubjects--Topical Terms:

757062
Metaheuristics.

LC Class. No.: QA76.9.A43 / R363 2019

Dewey Class. No.: 005.1

Metaheuristics for data clustering and image segmentation
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