Metaheuristics for Data Clustering and Image Segmentation (Hardcover, 1st ed. 2019)

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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.

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Product Description

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.

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Product Details

General

Imprint

Springer Nature Switzerland AG

Country of origin

Switzerland

Series

Intelligent Systems Reference Library, 152

Release date

2019

Availability

Expected to ship within 10 - 15 working days

First published

2019

Authors

,

Dimensions

235 x 155mm (L x W)

Format

Hardcover

Pages

163

Edition

1st ed. 2019

ISBN-13

978-3-03-004096-3

Barcode

9783030040963

Categories

LSN

3-03-004096-8



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