Data Mining System Based On Rough Set Neural Network And Its Application

In the process of designing the"digitized community integrative"platform, massive data are stored in data base. In order to fully utilize the data, excavate the underlying rules from them and better improve the function of digitized community and integrative platform, we designed a data mining system based on rough sets artificial neural networks.Data mining is a method to excavate implicit and unknown knowledge and rules, which possess potential values in decision making, from massive data. Those rules contain special relations among a set of certain objects in the data base. The patterns can provide valuable information in operational decision making, marketing and financial predictions.Common algorithms and theories used in data mining include rough sets, artificial neural networks, decision trees and genetic algorithms.Artificial neural network is one of the most commonly used algorithms in data mining. It has the advantages of a high accuracy, a great anti-yawp capacity and a low error rate in calculation. However, artificial neural network also has its disadvantage in that it has a relatively complicated structure, a longer training period and a deficiency in calculation report interpretation. This paper proposed a new (data mining) method in which a preprocessing of the data using rough sets theory will be followed by data mining using neural rules. With a limited decrease in accuracy, this method provides us with clear, definite and low error rate associate rules, as well as a shorter network training time. The proposed method thus eliminates some of the system limitations caused by of an exclusive/sole application of artificial neural networkThis paper employs advanced data mining technique to build a data mining...