Incorporating Hard and Soft Data into a Model for Evaluation of Local Environment

S. Kawano, Y. Takeda, V.N. Huynh, and Y. Nakamori (Japan)


Environmental modeling, fuzzy clustering, context model, context-based fuzzy model.


This paper aims at incorporating hard and soft data into a rule-based model for evaluation of local environment, where by hard data we mean the statistical measurements while by soft data we mean subjective appreciation of hu man beings of environmental issues. As people’s feel ing strongly depends on the social and economical char acteristics of regions where they live, we first use the hard data concerning these characteristics to do clustering in or der to obtain clusters corresponding to regions with the homogeneous social and economical characteristics rela tively. Based on the notion of context model, we then de velop a fuzzy model for evaluation of local environment in Ishikawa prefecture in Japan. It is shown that the soft data is rather reliable and we should integrate subjective knowl edge learned from soft data into modeling of environmental issues.

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