Papers by Author: Xin Cai Gu

Abstract: This paper designs a new outlier mining algorithm based on distance through introducing the "key attribute", which reduces the amount of data mining and increases the efficiency of outlier mining, simultaneously, improves the common distance measure and calculates with the improved Modifing Weighted Manhattan Distance(MWMD), the improved mining algorithm cancels the requirements of the parameter setting in the case of without affecting the mining results and gives the isolation degree of outliers.

Abstract: In this paper, we present a solution developed at rough set theory and weight value to make multiattribute decision with incomplete information. The paper defined the concepst of breaking points and recovered the incomplete information system according to the relationship between the condition attributes and decision attributes. And introduced OWGA(ordered weight geometric averaging) operators to calculate the aggregation value of each project. Finally, selected the project with the maximum aggregation value as the best decision making. The illustration and experiments were implemented and the results indicate that the method is effective and efficient.