A Data Mining And Decision Support System For Rehabilitation Of Disabled Persons

With the increasing development of information technology, we have entered an era of mass data, how to use these complex data to obtain the necessary information and analysis has become an inevitable challenge. The number of disabled information of our country is numerous, large, and with complex structures, in order to better building around the disabled social security system and service system, mining and analysis of data for the rehabilitation of the disabled has played a crucial role, through mining and analysis the related data can strengthen the social, institutional, personal to understand of the rehabilitation of the disabled. At the same time, it can also provide the technical support for the implementation of the policy with medical care for disabled. For patients and their families, through the prediction and analysis of rehabilitation, to better grasp the information of rehabilitation. So the excavation and analysis of data for the rehabilitation of the disabled has become an important research topic in the field of rehabilitation of the disabled.The purpose of this paper is to study the rehabilitation of disabled persons through the data, to design and implement the data mining and decision making system for disabled persons, mainly including two aspects: classification and prediction. In the aspect of the classification with the rehabilitation data, we application classification algorithms to establish the corresponding decision model, realize the classification for the rehabilitation data of the disabled, description and show the process of classification. On the prediction of rehabilitation information, this paper through the analysis of the data, using correlation algorithm to predicts the trend of rehabilitation, to play an important role in the way of rehabilitation. At the same time the visualization of classification data mining results and realize the related design, make the results more intuitive and simple to understand, were compared before and after using the result of forecasting, makes the conclusion appears more concrete and vivid.