Intelligent Search Mechanism Based on Neuro-Fuzzy System for the Distributed Object Groups

Intelligent systems introduce methods of extracting rules from data and construct models for optimizing the use of resources. In distributed environment, object group models are designed for the system scalability and accessibility of the objects to each group. However, dynamic grouping using knowledge extraction from group of objects is not considered which provides efficient search for appropriate objects. In this paper, a distributed and intelligent framework is presented to address the use of intelligent models in distributed object groups. The focus of this paper is the intelligent search mechanism based on neuro-fuzzy system. To have an accurate classification in searching appropriate objects, the fuzzy system is adjusted by neuro-fuzzy algorithm. A simulation of the proposed framework based in CORBA implementation is presented. The proposed method is compared to other methods in accuracy of classification and result shows that it outperformed other algorithm based on processing time and epoch counts.