@article{(Open Science Index):https://publications.waset.org/pdf/5810,
	  title     = {Mamdani Model based Adaptive Neural Fuzzy Inference System and its Application},
	  author    = {Yuanyuan Chai and  Limin Jia and  Zundong Zhang},
	  country	= {},
	  institution	= {},
	  abstract     = {Hybrid algorithm is the hot issue in Computational
Intelligence (CI) study. From in-depth discussion on Simulation
Mechanism Based (SMB) classification method and composite patterns,
this paper presents the Mamdani model based Adaptive Neural
Fuzzy Inference System (M-ANFIS) and weight updating formula in
consideration with qualitative representation of inference consequent
parts in fuzzy neural networks. M-ANFIS model adopts Mamdani
fuzzy inference system which has advantages in consequent part.
Experiment results of applying M-ANFIS to evaluate traffic Level
of service show that M-ANFIS, as a new hybrid algorithm in computational
intelligence, has great advantages in non-linear modeling,
membership functions in consequent parts, scale of training data and
amount of adjusted parameters.},
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {3},
	  number    = {3},
	  year      = {2009},
	  pages     = {663 - 670},
	  ee        = {https://publications.waset.org/pdf/5810},
	  url   	= {https://publications.waset.org/vol/27},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 27, 2009},
	}