The application of data mining techniques and processes based on standard CRISP-DM in order to discover hidden knowledge by using neural networks

In this research, the applied research - is descriptive data 1394 137 system using software to perform data mining process Clementine 12 is used. One result of this study was to determine homogeneous regions in terms of system 137 using the clustering technique into two categories, which indicate areas where the latter were prepared and awareness to communicate with the system and the call up of citizens these areas, the problem is most of them. In addition, using the association rules correlation between the problem areas and areas have been investigated and determined which areas in each region more prone to problems and urban problems that can otherwise be prepared stifled by them. In addition, results interesting patterns also predict the number of calls related to flooded and water Disability region based on the amount of rainfall or determine the dependence of inquiry flooded between different parts of a particular area lost. Expected results in the management of urban problems and increasing the level of citizens satisfaction with work.

Keywords:

data mining , clustering , Association rules , neural network