de Sourav, Dey Sandip, Bhattacharyya Siddhartha Recent Advances in Hybrid Metaheuristics for Data Clustering 9781119551591

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Автор: de Sourav, Dey Sandip, Bhattacharyya Siddhartha (Дей ле Сурав)
Название: Recent Advances in Hybrid Metaheuristics for Data Clustering
Перевод названия: Дей ле Сурав: Последние достижения в гибридной метаэвристике для кластеризации данных
ISBN: 9781119551591
Издательство: Wiley
Классификация:

Гражданское строительство, обследование участков и стройка

Алгоритмы и структуры данных

ISBN-10: 1119551595
Обложка/Формат: Hardcover
Страницы: 200
Вес: 0.51 кг.
Дата издания: 24.08.2020
Серия: The wiley series in intelligent signal and data processing
Язык: English
Размер: 249 x 170 x 17
Читательская аудитория: Professional & vocational
Ссылка на Издательство: Link
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Поставляется из: Англии
Описание:

An authoritative guide to an in-depth analysis of various state-of-the-art data clustering approaches using a range of computational intelligence techniques

Recent Advances in Hybrid Metaheuristics for Data Clustering offers a guide to the fundamentals of various metaheuristics and their application to data clustering. Metaheuristics are designed to tackle complex clustering problems where classical clustering algorithms have failed to be either effective or efficient. The authors--noted experts on the topic--provide a text that can aid in the design and development of hybrid metaheuristics to be applied to data clustering.

The book includes performance analysis of the hybrid metaheuristics in relationship to their conventional counterparts. In addition to providing a review of data clustering, the authors include in-depth analysis of different optimization algorithms. The text offers a step-by-step guide in the build-up of hybrid metaheuristics and to enhance comprehension. In addition, the book contains a range of real-life case studies and their applications. This important text:

Includes performance analysis of the hybrid metaheuristics as related to their conventional counterparts
Offers an in-depth analysis of a range of optimization algorithms
Highlights a review of data clustering
Contains a detailed overview of different standard metaheuristics in current use
Presents a step-by-step guide to the build-up of hybrid metaheuristics
Offers real-life case studies and applications

Written for researchers, students and academics in computer science, mathematics, and engineering, Recent Advances in Hybrid Metaheuristics for Data Clustering provides a text that explores the current data clustering approaches using a range of computational intelligence techniques.

Recent Advances in Hybrid Metaheuristics for Data Clustering, de Sourav, Dey Sandip, Bhattacharyya Siddhartha