Metaheuristics for Data Clustering and Image Segmentation

✍ Scribed by Meera Ramadas, Ajith Abraham

Publisher: Springer International Publishing
Year: 2019
Tongue: English
Leaves: 167
Series: Intelligent Systems Reference Library 152
Edition: 1st ed.
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

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.

✦ Table of Contents

Front Matter ....Pages i-ix
Introduction (Meera Ramadas, Ajith Abraham)....Pages 1-5
Metaheuristics and Data Clustering (Meera Ramadas, Ajith Abraham)....Pages 7-55
Revised Mutation Strategy for Differential Evolution Algorithm (Meera Ramadas, Ajith Abraham)....Pages 57-65
Search Strategy Flower Pollination Algorithm with Differential Evolution (Meera Ramadas, Ajith Abraham)....Pages 67-94
Forced Strategy Differential Evolution Used for Data Clustering (Meera Ramadas, Ajith Abraham)....Pages 95-119
Reconstructed Mutation Strategy for Differential Evolution Algorithm (Meera Ramadas, Ajith Abraham)....Pages 121-135
Enhanced Differential Evolution with Fuzzy c-Means Technique (Meera Ramadas, Ajith Abraham)....Pages 137-153
Conclusion and Future Scope (Meera Ramadas, Ajith Abraham)....Pages 155-156
Back Matter ....Pages 157-163

✦ Subjects

Engineering; Computational Intelligence; Image Processing and Computer Vision; Algorithms

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