Fuzzy-genetic Hybrids

Fuzzy systems have been integrated with GAs. The fuzzy systems like NNs (feed forward) are universal approximator in the sense that they exhibit the capability to approximate general nonlinear functions to any desired degree of accuracy. The adjustments of system parameters called for in the process, so that the system output matches the training data, have been tackled using GAs. Several parameters which a fuzzy system is involved with like input/output variables and the membership function that define the fuzzy systems have been optimized using GAs.

Typical Hybrid Systems

The Systems considered are listed below.

1. Genetic algorithm based back propagation network (Neuro Genetic Hybrid)

2. Fuzzy back propagation network (Neuro – Fuzzy Hybrid with Multilayer Feed forward Network as the host architecture)

3. Simplified Fuzzy ARTMAP (Neuro – Fuzzy Hybrid with Recurrent Network as the host architecture)

4. Fuzzy Associative Memory (Neuro – Fuzzy Hybrid with single layer Feed forward architecture)

5. Fuzzy logic controlled Genetic algorithm (Fuzzy – Genetic Hybrid)