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Fuzzy Rule–Based Approach for Detection of Bounded Weak-Echo Regions in Radar Images

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  • 1 Electronics and Communication Sciences Unit, Indian Statistical Institute, Calcutta, India
  • | 2 Gitanjali Net, Visva-Bharati University, Santiniketan, India
  • | 3 Electronics and Communication Sciences Unit, Indian Statistical Institute, Calcutta, India
  • | 4 National Severe Storms Laboratory, University of Oklahoma, Norman, Oklahoma
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Abstract

A method for the detection of a bounded weak-echo region (BWER) within a storm structure that can help in the prediction of severe weather phenomena is presented. A fuzzy rule–based approach that takes care of the various uncertainties associated with a radar image containing a BWER has been adopted. The proposed technique automatically finds some interpretable (fuzzy) rules for classification of radar data related to BWER. The radar images are preprocessed to find subregions (or segments) that are suspected candidates for BWERs. Each such segment is classified into one of three possible cases: strong BWER, marginal BWER, or no BWER. In this regard, spatial properties of the data are being explored. The method has been tested on a large volume of data that are different from the training set, and the performance is found to be very satisfactory. It is also demonstrated that an interpretation of the linguistic rules extracted by the system described herein can provide important characteristics about the underlying process.

Corresponding author address: Prof. Nikhil R. Pal, Electronics and Communication Sciences Unit, Indian Statistical Institute, 203 B.T. Road, Calcutta 700108, India. Email: nikhil@isical.ac.in

Abstract

A method for the detection of a bounded weak-echo region (BWER) within a storm structure that can help in the prediction of severe weather phenomena is presented. A fuzzy rule–based approach that takes care of the various uncertainties associated with a radar image containing a BWER has been adopted. The proposed technique automatically finds some interpretable (fuzzy) rules for classification of radar data related to BWER. The radar images are preprocessed to find subregions (or segments) that are suspected candidates for BWERs. Each such segment is classified into one of three possible cases: strong BWER, marginal BWER, or no BWER. In this regard, spatial properties of the data are being explored. The method has been tested on a large volume of data that are different from the training set, and the performance is found to be very satisfactory. It is also demonstrated that an interpretation of the linguistic rules extracted by the system described herein can provide important characteristics about the underlying process.

Corresponding author address: Prof. Nikhil R. Pal, Electronics and Communication Sciences Unit, Indian Statistical Institute, 203 B.T. Road, Calcutta 700108, India. Email: nikhil@isical.ac.in

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