Discovering Rules from Data for Water Demand Prediction
نویسندگان
چکیده
Prediction of consumer demands is a pre-requisite for optimal control of water distribution systems. In this paper, we present a rough set method for generating prediction rules from a set of observed data. The proposed method is based on an extension of the standard rough set model. The salient feature of this method is that it makes use of the statistical information inherent in the data to handle incomplete and ambiguous training samples. Experimental results from using this method for water demand prediction are given.
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