Decision Support System Model Based On Rough Set

Rough sets is a mathematical tools deal with imprecise, uncertain and incomplete data. Decision support system for supporting decision and rough set for information processing capabilities have become increasingly exposed and concern for people. This paper studies the decision support system model based on rough set theory. That the Decision Support System is using rough set for data processing.This paper studies rough set and decision support system concepts and associated knowledge, and research rough sets and decision support systems for the status and development of in-depth study. The concept of rough set is proposed in 1982 by Pawlak Z. The basic idea is summarized concepts and rules by the Case Library classification. Conditions of the library through case characteristic variables make the case base classification form the concept. Study the target feature to be decision rules by generating the concept. Decision support system is to assist decision through the data, models and knowledge. it is a semi-structured or unstructured decision computer application system though human-computer interaction approach. It provides decision-makers environmental of analyze problems, build models, simulating decision processes and programs. Help policy makers to improve decision level and quality with a variety of information resources and analytical tools.This paper study the Shanghai A Shares for more than 800 stocks as an object. The stock Decision Support System Model is proposed based on rough set. The stock model of decision support system based on rough set is conducted a preliminary design. It discussed the function of each module. It describes the method of processing the data using rough set. Stock information system is inconsistent decision information system. It gets decision rules processing inconsistent decision information system in the rough set attribute reduction method of. Through the validation arrive at the correct of the decision rules.