The New Method Definite Initial Cluster Center for Fuzzy Risk Clustering Neural Networks

DOI

10.2991/iske.2007.64How to use a DOI?

Keywords

density; grid; initial cluster center; fuzzy risk clustering neural networks

Abstract

Neural network has a powerful parallel processing capability, along with its rise in the fuzzy risk cluster analysis which has occupied an important position, however, the quality of fuzzy risk clustering results is influenced by the initial value of options. The initial cluster center method for fuzzy risk clustering neural network, based on density and grid method, automatically determine the number of clusters and the initial cluster centers. Compared with the classical method simulation FCM, we can see a valid and effective method that can effectively speed up the convergence.

Copyright

© 2007, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Kaiqi Zou
AU  - Jie Cui
PY  - 2007/10
DA  - 2007/10
TI  - The New Method Definite Initial Cluster Center for Fuzzy Risk Clustering Neural Networks
BT  - Proceedings of the 2007 International Conference on Intelligent Systems and Knowledge Engineering (ISKE 2007)
PB  - Atlantis Press
SP  - 381
EP  - 384
SN  - 1951-6851
UR  - https://doi.org/10.2991/iske.2007.64
DO  - 10.2991/iske.2007.64
ID  - Zou2007/10
ER  -