@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}, }