Classification of Indian meteorological stations using cluster and fuzzy cluster analysis, and Kohonen artificial neural networks

Raju, K Srinivasa and Kumar, D Nagesh (2007) Classification of Indian meteorological stations using cluster and fuzzy cluster analysis, and Kohonen artificial neural networks. In: Nordic Hydrology, 38 (3). pp. 303-314.

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Abstract

The present study deals with the application of cluster analysis, Fuzzy Cluster Analysis (FCA) and Kohonen Artificial Neural Networks (KANN) methods for classification of 159 meteorological stations in India into meteorologically homogeneous groups. Eight parameters, namely latitude, longitude, elevation, average temperature, humidity, wind speed, sunshine hours and solar radiation, are considered as the classification criteria for grouping. The optimal number of groups is determined as 14 based on the Davies-Bouldin index approach. It is observed that the FCA approach performed better than the other two methodologies for the present study.

Item Type:	Journal Article
Publication:	Nordic Hydrology
Publisher:	IWA Publishing
Additional Information:	Copyright of this article belongs to IWA Publishing.
Department/Centre:	Division of Mechanical Sciences > Civil Engineering
Date Deposited:	12 Mar 2010 06:47
Last Modified:	19 Sep 2010 05:56
URI:	http://eprints.iisc.ac.in/id/eprint/26132

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