Papers by Author: Liang Shan Shao

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.

Abstract: To attribute reduction in an uncertain information system, this paper proposed a method of attribute reduction based on rough set theory. This reduction method gives the concepts of tolerance relationship, attribute significance and tolerance relationship similar matrix to deal with the inconsistency problem of in the information table. And then obtains the core attributes of incomplete information systems via the tolerance relationship similar matrix. Finally, according to attribute frequency in the tolerance relationship similar matrix, as the heuristic knowledge, makes use of binsearch heuristic algorithm to calculate the candidate attribute expansion so that it can reduce the expansion times to speed up reduction. Experiment results show that the algorithm is simple and effective.