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An interpretable fuzzy monthly rainfall spatial interpolation system for the construction of aerial rainfall maps

Kajornrit, J., Wong, K.W. and Fung, C.C. (2016) An interpretable fuzzy monthly rainfall spatial interpolation system for the construction of aerial rainfall maps. Soft Computing, 20 (12). pp. 4631-4643.

Link to Published Version: http://dx.doi.org/10.1007/s00500-014-1456-9
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Abstract

Spatial interpolation methods are normally used to create aerial rainfall maps from remote measuring data collected by raingauge network. However, most spatial interpolation methods are not in the form of interpretable data models. This could make further analysis on the spatial data difficult. This paper proposes a methodology to analyze and establish an interpretable fuzzy model for monthly rainfall spatial interpolation. The proposed methodology integrates the benefits of various soft computing techniques. The final outcome is the proposal of an interpretable fuzzy model that allows human analysts to gain insight into the spatial data to be modeled. The accuracy of the model is evaluated by eight monthly rainfall data in the northeast region of Thailand. The interpretability of the model is assessed by the interpretable fuzzy modeling criteria. The experimental results showed that the proposed methodology could be an alternative technique to create rainfall maps and to understand the characteristics of the spatial data.

Publication Type: Journal Article
Murdoch Affiliation: School of Engineering and Information Technology
Publisher: Springer Berlin
Copyright: © 2014 Springer-Verlag Berlin Heidelberg
URI: http://researchrepository.murdoch.edu.au/id/eprint/26198
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