Rough set approach to sunspot classification problem

Authors:
Sinh Hoa Nguyen;Trung Thanh Nguyen;Hung Son Nguyen
Affiliations:
Polish-Japanese Institute of Information Technology, Warsaw, Poland;Department of Computer Science, University of Bath, Bath, United Kingdom;Institute of Mathematics, Warsaw University, Warsaw, Poland
Venue:
RSFDGrC'05 Proceedings of the 10th international conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing - Volume Part II
Year:
2005

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Abstract

This paper presents an application of hierarchical learning method based rough set theory to the problem of sunspot classification from satellite images. The Modified Zurich classification scheme [3] is defined by a set of rules containing many complicated and unprecise concepts, which cannot be determined directly from solar images. The idea is to represent the domain knowledge by an ontology of concepts – a treelike structure that describes the relationship between the target concepts, intermediate concepts and attributes. We show that such ontology can be constructed by a decision tree algorithm and demonstrate the proposed method on the data set containing sunspot extracted from satellite images of solar disk.