Research On Rough Set Theory And Application In Higher Edueation Evaluation

Quantitative method is one of the most important methods of higher edueation evaluation. Because of the complexity and dynamic of the environment, the evaluation subject has to deal with diverse and uncertain data, and the traditional methods could not meet the practical requirements of the higher education evaluation. This paper mainly discusses methods of higher edueation evaluation based on rough set theory. New expansion of dominance relations such as limited dominance relation, definitive dominance relation and limited similarity dominance relation are proposed for multi-attribute decision making problems with preference and incomplete information. For the results of attribute reduction are not unique, a preferred method in which conditional information entropy is used to measure reduction of attributes is proposed. Intrinsic relationship between attributes reduction relation of rough sets and classification of universe is researched and an efficient attribute reduction algorithm of rough sets based on classification merging is given by using an invariance of positive region of some rough sets. Based on the research on rough set theory, the empirical analysis of the talents cultivation level assessment project for higher technical and vocational institution of Jiangsu province are made. The main innovations of the paper are as follows:(1) In the incomplete information decision-making system, the limited dominance relation and definitive dominance relation proposed are more rationally to deal with the known and unknown attribute values. Based on the limited dominance-based and definitive dominance-based rough sets, two types of knowledge reductions are proposed. Then, the practical approaches to compute the reductions are presented. One can obtain higher quality of decision rules by using the limited dominance-based and definitive dominance-based rough sets model.(2) The concept of definitive dominance relation and limited similarity dominance relation are proposed in the rough fuzzy set. And based on above new extended dominance relations, two types of knowledge reductions are proposed. Then, the practical approaches to compute the reductions are presented."At least"and"at most"rules can be obtained by using definitive dominance-based and limited similarity dominance-based rough sets model in the incomplete fuzzy objective information system.(3) In order to exclude the interference of the noise factor, based on definitive dominance relation, an analysis method of decision-making based on variable precision rough set is proposed. Then, the disadvantages of the current conditional information entropy are analyzed when conditional information entropy is used to measure reduction of attributes of dominance-based rough sets. Variable precision rough set theory is used as a basis for proposing a new condition information, with another parameter choosed. Then, a new algorithm based on new condition information entropy is designed to choose reduction of attributes of Variable precision dominance rough set, which is better than others.(4) Intrinsic relationship between attributes reduction relation of rough set and classification of universe is researched through one to one mapping relation between classification of universe and equivalence relation determined by subset of attribute set. Using an invariance of positive region of some rough sets, an efficient attribute reduction algorithm of rough set based on classification merging is proposed.(5) Based on the decision-making theory and the research on rough set theory, the empirical analysis of the talents cultivation level assessment project for higher technical and vocational institution of Jiangsu province are made. The Inherent discipline between the class 1 index and the general evaluation is revealed which can provide some valuable decision-making information and policy recommendations for educational authorities, evaluation agency and assessed institutions.