On designing a fuzzy control system using an optimization algorithm
Fuzzy Sets and Systems
Identifying fuzzy models utilizing genetic programming
Fuzzy Sets and Systems
Modeling and control of a pilot pH plant using genetic algorithm
Engineering Applications of Artificial Intelligence
GA-TSKfnn: Parameters tuning of fuzzy neural network using genetic algorithms
Expert Systems with Applications: An International Journal
Evolutionary design of fuzzy rule base for nonlinear system modeling and control
IEEE Transactions on Fuzzy Systems
Optimal fuzzy controller design: local concept approach
IEEE Transactions on Fuzzy Systems
| Hi-index | 12.05 |
In this paper, we have prospered a new method to generate fuzzy rules using a genetic algorithm, back propagation, and fuzzy neural networks (FNN) algorithm for seismic reservoir fuzzy rules extraction. This method aims to combine the advantages of fuzzy systems (FS), artificial neural networks (ANN), and GA algorithms and to remedy their drawbacks. The hybrid algorithm can optimize not the number of rules but the membership functions of the antecedent and consequent by adopting multi-encoding of GA. Fuzzy IF/THEN rules were extracted from the optimized FNN.The extracted rules can help to reason the reservoir thickness and decide the optimal drill position in oil field exploration.