Combination Of Rough Set And Neural Network Data Fusion Research

With the rapid development of information science, new and higher requirement is presented to data processing technique. Influenced by such factors as the precision of sensors, the cost of data collection, the variety of data mode and the external environment, the information in multi-sensor system is mostly incomplete. As a result, the traditional data processing methods can't satisfy the demands of high precision and rapid speed of information processing, which brings new challenge to data fusion. Therefore, the processing of incomplete information in multi-sensor system has been a hot spot concerned by many scholars. With the method of combing data mining and data fusion technology, the dissertation researches the processing method of incomplete information.The main work and innovations are as follows:Firstly, according to the complementary functions of data fusion and data mining, the basic concepts and the principle of combining both technologies are investigated. Moreover, in order to deal with the redundant data and the difficulty of obtaining prior knowledge, the fusion model based on rough sets is studied. By applying the reduction method, the redundant information is eliminated and the fusion algorithm is extracted.Secondly, a discretization method based on genetic algorithm is proposed. In this method, the minimum set of cuts and the maximum consistency of decision system are the optimizing goals. Thus the consistency of the system is ensured at the maximal extent.Thirdly, a data mining method based on rough sets theory for incomplete information system is proposed. From the practical application, in consideration of the real-time, difficulty and cost during obtaining the attributes, the attributes are partitioned into complete part and incomplete part. Thus the decision system is presented at two layers. Then the reduction method is hierarchically applied to each layer. This mining method has strong application and fast reduction speed.Finally, the problem of incomplete information in multi-sensor system is investigated. By combining the above mining method and neural network, a design...