Metaheuristics for Data Clustering and Image Segmentation

1. Auflage 2019
ISBN: 978-3-030-04096-3
Verlag: Springer International Publishing

Buch, Englisch, Band 152, 163 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 436 g

Reihe: Intelligent Systems Reference Library

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.

Zielgruppe

Research

Autoren/Hrsg.

Abraham, Ajith

Ramadas, Meera

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Computer Vision
• Mathematik | Informatik EDV | Informatik Informatik Bildsignalverarbeitung
• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Algorithmen & Datenstrukturen

Inhaltsverzeichnis

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