IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Performance Analysis of DE over K-Means Proposed Model of Soft Computing

Performance Analysis of DE over K-Means Proposed Model of Soft Computing
View Sample PDF
Author(s): Kapil Patidar (Amity School of Engineering and Technology, India), Manoj Kumar (Amity School of Engineering and Technology, India)and Sushil Kumar (Amity School of Engineering and Technology, India)
Copyright: 2017
Pages: 14
Source title: Artificial Intelligence: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-5225-1759-7.ch095

Purchase

View Performance Analysis of DE over K-Means Proposed Model of Soft Computing on the publisher's website for pricing and purchasing information.

Abstract

In real world data increased periodically, huge amount of data is called Big data. It is a well-known term used to define the exponential growth of data, both in structured and unstructured format. Data analysis is a method of cleaning, altering, learning valuable statistics, decision making and advising assumption with the help of many algorithm and procedure such as classification and clustering. In this chapter we discuss about big data analysis using soft computing technique and propose how to pair two different approaches like evolutionary algorithm and machine learning approach and try to find better cause.

Related Content

Kamel Mouloudj, Vu Lan Oanh LE, Achouak Bouarar, Ahmed Chemseddine Bouarar, Dachel Martínez Asanza, Mayuri Srivastava. © 2024. 20 pages.
José Eduardo Aleixo, José Luís Reis, Sandrina Francisca Teixeira, Ana Pinto de Lima. © 2024. 52 pages.
Jorge Figueiredo, Isabel Oliveira, Sérgio Silva, Margarida Pocinho, António Cardoso, Manuel Pereira. © 2024. 24 pages.
Fatih Pinarbasi. © 2024. 20 pages.
Stavros Kaperonis. © 2024. 25 pages.
Thomas Rui Mendes, Ana Cristina Antunes. © 2024. 24 pages.
Nuno Geada. © 2024. 12 pages.
Body Bottom