2015
DOI: 10.5120/ijca2015905635
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Abstract: In this paper, we presented the architecture and basic learning process underlying ANFIS (adaptive-network-based fuzzy inference system) which is a fuzzy inference system implemented in the framework of adaptive networks. Soft computing approaches including artificial neural networks and fuzzy inference have been used widely to model expert behavior. Using given input/output data values, the proposed ANFIS can construct mapping based on both human knowledge (in the form of fuzzy if-then rules) and hybrid learn… Show more

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Cited by 138 publications
(82 citation statements)
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References 20 publications
(41 reference statements)
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“…The grey fuzzy neural network is newly designed with the aid of [17] grey wolf Optimizer (GWO) and adaptive neuro-fuzzy inference system (ANFIS) [18]. In ANFIS, the training algorithm is altered with the grey wolf optimizer algorithm.…”
Section: Proposed Grey Fuzzy Neural Networkmentioning
confidence: 99%
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“…The grey fuzzy neural network is newly designed with the aid of [17] grey wolf Optimizer (GWO) and adaptive neuro-fuzzy inference system (ANFIS) [18]. In ANFIS, the training algorithm is altered with the grey wolf optimizer algorithm.…”
Section: Proposed Grey Fuzzy Neural Networkmentioning
confidence: 99%
“…Initially, the premise parameters are optimized to fix the values using GWO algorithm. Once the premise parameters are fixed, then the final output [18] is expressed by the combination of the linear parameter.…”
Section: Proposed Gfnnmentioning
confidence: 99%
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