Paper Title:
A K-Means Clustering Algorithm Based on Enhanced Differential Evolution
  Abstract

The conventional k-means algorithms are sensitive to the initial cluster centers, and tend to be trapped by local optima. To resolve these problems, a novel k-means clustering algorithm using enhanced differential evolution technique is proposed in this paper. This algorithm improves the global search ability by applying Laplace mutation operator and exponentially increasing crossover probability operator. Numerical experiments show that this algorithm overcomes the disadvantages of the conventional k-means algorithms, and improves search ability with higher accuracy, faster convergence speed and better robustness.

  Info
Periodical
Chapter
Chapter 1: Measure Control Technologies and Intelligent Systems
Edited by
Zhijiu Ai, Xiaodong Zhang, Yun-Hae Kim and Prasad Yarlagadda
Pages
71-75
DOI
10.4028/www.scientific.net/AMR.339.71
Citation
L. Mao, H. J. Gong, X. Y. Liu, "A K-Means Clustering Algorithm Based on Enhanced Differential Evolution", Advanced Materials Research, Vol. 339, pp. 71-75, 2011
Online since
September 2011
Export
Price
$32.00
Share

In order to see related information, you need to Login.

In order to see related information, you need to Login.

Authors: Na Rui Bu, Run Shan Bai, Zhang Zhen Li, De Zhong Lin
Chapter 6: Vibration, Noise Analysis and Control
Abstract:Analysis of slope stability based on BP neural network, the analytical model of slope stability is built. Aiming at the defects that BP...
1263
Authors: Da Wang, Hong Yu Bian
Chapter 1: Mechatronics
Abstract:In order to further improve the accuracy of the sonar image registration, a novel hybrid algorithm was proposed. It proposed the normalized...
1811
Authors: Si Lian Xie, Tie Bin Wu, Shui Ping Wu, Yun Lian Liu
Chapter 18: Computer Applications in Industry and Engineering
Abstract:Evolutionary algorithms are amongst the best known methods of solving difficult constrained optimization problems, for which traditional...
2846
Authors: Rui Ni Li, Xiao Yi Wang, Zai Wen Liu, Ji Ping Xu, Ling Bin Wang
Chapter 4: Waste Disposal and Recycling
Abstract:Various unusual conditions are likely to occur during sewage treatment process, which would lead to some consequences such as the decrease of...
622
Authors: Hai Yan Wang
Chapter 6: Production Management
Abstract:This paper presents a hybrid algorithm to address the flexible job-shop scheduling problem (FJSP). Based on Differential Evolution (DE), a...
502