الفهرس 
IntroductionOnly 14 pages are availabe for public view
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Abstract
This thesis proposes a new intelligent data analysis method for generating classification model by using rough set theory, gene expression programming and rough neural networks. The new presented model named Gene Expression Programming Rough Neural Networks (GEP-RNN). Worldwide, there has been a rapid growth in interest in rough set theory and its applications in recent years. Evidence of this can be found in the increasing number of high-quality articles on rough sets and related topics that have been published in a variety of international journals, symposia, workshops and international conference. In addition, many international workshops and conferences have included special sessions on the theory and applications of rough sets, it has been applied in several fields including image processing, data mining, pattern recognition, medical informatics, knowledge discovery and expert systems.