Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1016/j.eswa.2009.06.074 | Expert Syst. Appl. |
Keywords | Field | DocType |
seismic reservoir,fuzzy neural network,fuzzy system,genetic algorithm,artificial neural network,fuzzy rules extraction,ga algorithm,hybrid algorithm,multi-encoding,optimized fnn,fuzzy logic,neuro-fuzzy ga-bp method,new method,fuzzy rule,back propagation,membership function,neuro fuzzy | Data mining,Neuro-fuzzy,Fuzzy classification,Defuzzification,Fuzzy set operations,Computer science,Fuzzy logic,Artificial intelligence,Adaptive neuro fuzzy inference system,Fuzzy associative matrix,Fuzzy number,Machine learning | Journal |
Volume | Issue | ISSN |
37 | 3 | Expert Systems With Applications |
Citations | PageRank | References |
6 | 0.76 | 12 |
Authors | ||
4 | ||