Computer Science – Artificial Intelligence
Scientific paper
2004-05-04
Recent Advances in Intelligent Paradigms and Applications, Abraham A., Jain L. and Kacprzyk J. (Eds.), Studies in Fuzziness an
Computer Science
Artificial Intelligence
Scientific paper
The integration of different learning and adaptation techniques to overcome individual limitations and to achieve synergetic effects through the hybridization or fusion of these techniques has, in recent years, contributed to a large number of new intelligent system designs. Computational intelligence is an innovative framework for constructing intelligent hybrid architectures involving Neural Networks (NN), Fuzzy Inference Systems (FIS), Probabilistic Reasoning (PR) and derivative free optimization techniques such as Evolutionary Computation (EC). Most of these hybridization approaches, however, follow an ad hoc design methodology, justified by success in certain application domains. Due to the lack of a common framework it often remains difficult to compare the various hybrid systems conceptually and to evaluate their performance comparatively. This chapter introduces the different generic architectures for integrating intelligent systems. The designing aspects and perspectives of different hybrid archirectures like NN-FIS, EC-FIS, EC-NN, FIS-PR and NN-FIS-EC systems are presented. Some conclusions are also provided towards the end.
No associations
LandOfFree
Intelligent Systems: Architectures and Perspectives does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Intelligent Systems: Architectures and Perspectives, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Intelligent Systems: Architectures and Perspectives will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-467083