Extracting Spatial Decision Rules Using Rough Fuzzy Sets

Hexiang Bai and Yong Ge*
State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Science, Beijing, China

Abstract: Rough sets and fuzzy sets have been widely used in the spatial analysis. Classical rough set theory has no ability to handle fuzzy uncertainty while rough fuzzy set can deal with the case when the conditional attributes are crisp and the decision attributes are fuzzy concepts in the decision information system. This type of decision information system is called a fuzzy decision information system. Rough fuzzy set are specialized in analyzing fuzzy decision information system. Based on the rough fuzzy set, this paper proposes a new method to extract the spatial fuzzy decision rules. This new method first converts sample data into a fuzzy decision information system from which spatial fuzzy decision rules are extracted. Then the conditional attributes in the fuzzy decision information system are then discretized. Third, the fuzzy decision information system is reducted. The conditional attributes selected are used to extract fuzzy decision rules in the discretized fuzzy decision information system. Finally these rules can be used to predict spatial objects with no fuzzy decisions. The general process of this method has been demonstrated by an example.

Keywords: Rough fuzzy set; spatial fuzzy decision rule; spatial data analysis component

BaiAccuracy2010.pdf356.34 KB