Intelligent adaptation process for case based systems

Abstract EN

Case Based Reasoning (CBR) Systems is one of the important decision making systems applied in many fields all over the world.

The effectiveness of any CBR system based on the quality of the storage cases in the case library.

Similar cases can be retrieved and adapted to produce the solution for the new problem.

One of the main issues faced the CBR systems is the difficulties of achieving the useful cases.

The proposed system introduces a new approach that uses the genetic algorithm (GA) technique to automate constructing the cases into the case library.

Also, it can optimize the best one to be stored in the library for the future uses.

However, the proposed system can avoid the problems of the uncertain and noisy cases.

Besides, it can simply the retrieving and adaptation processes.

So, it can improve the performance of the CBR system.

The suggested system can be applied for many real-time problems.

It has been applied for diagnosis the faults of the wireless network, diagnosis of the cancer diseases, diagnosis of the debugging of a software as cases of study.

The proposed system has proved its performance in this field.