Methodology, System Adaptation, Pattern recognition, Neural Network, Analytic Programming

This paper describes the methodology for system description and application so that the system can be managed using real time system adaptation. Here, we propose approaches relying on machine learning methods, which would enable to characterize key patterns and detect them in real time and in their altered form as well. Then, based on the pattern recognized, it is possible to apply a suitable intervention to system inputs so that the system responds in the desired way. Our aim is to develop and apply a hybrid approach based on machine learning methods, particularly based on soft-computing methods to identify patterns successfully and for the subsequent adaptation of the system. The main goal of the paper is to recognize important pattern and adapt the system?s behaviour based on the pattern desired way.