SKEDSOFT

Neural Network & Fuzzy Systems

Introduction:-Hybrid systems employ more than one technology to solve a problem. Hybridization of technologies can have pitfalls and therefore need to be done with care. If one technology can solve a problem then hybrid technology ought to be used only if its application results in a better solution. Hybrid systems have been classified as Sequential, Auxiliary and Embedded.

In Sequential hybrid system, the technologies are used in pipelining fashion. In Auxiliary hybrid system, one technology calls the other technology as subroutine. In Embedded hybrid system, the technologies participating appear to be fused totally.

Sequential Hybrid System:-In Sequential hybrid system, the technologies are used in pipelining fashion. Thus, one technology's output becomes another technology’s input and it goes on. However, this is one of the weakest forms of hybridization since an integrated combination of technologies is not present.

Example: A Genetic algorithm preprocessor obtains the optimal parameters for different instances of a problem and hands over the preprocessed data to a neural network for further processing.

Embedded Hybrid System:-In Embedded hybrid system, the technologies participating are integrated in such a manner that they appear intertwined. The fusion is so complete that it would appear that no technology can be used without the others for solving the problem.

Example: A NN-FL hybrid system may have an NN which receives fuzzy inputs, processes it and extracts fuzzy outputs as well.

Neural Networks, Fuzzy Logic, and Genetic Algorithms Hybrids:-Neural Networks, Fuzzy Logic, and Genetic Algorithms are three distinct technologies.

Each of these technologies has advantages and disadvantages. It is therefore appropriate that hybridization of these three technologies is done so as to overcome the weakness of one with the strength of other.