Combination of Cloud Model and Rough Set to Find Knowledge in IDSS for Intelligent Disaster Emergency Decision

Decision support system using data mining to find decision knowledge is called Intelligent Decision Support System(IDSS). Rough set as a data mining method commonly is used to find classification knowledge in IDSS. But the classic data mining based on rough set is short in dealing with the blank value data or data with the character of blurring and randomicity. Such data is called as imperfect data. In order to overcoming this shortcoming the method of combination of cloud model and rough set to find knowledge from imperfect data in IDSS is proposed. Firstly the cloud is used to depict the imperfect data by group decision. In the following, attribution generation based on cloud model is used to generate the upper concept layer. In this step the cloud model depicting the imperfect data is classified into the concept layer which is proximal to itself according to distance between two cloud models. Then rough set method is used to gain knowledge. Lastly an experiment is given to verify the validity of the method.