@inproceedings { , title = {An extended ANFIS architecture and its learning properties for type-1 and interval type-2 models}, abstract = {In this paper, an extended ANFIS architecture is proposed. By incorporating an extra layer for the fuzzification process, the extended architecture is able to fit both type-1 and interval type-2 models. The learning properties of the proposed architecture based on the least-squares estimate method are studied on selected type-1 and interval type-2 ANFIS models. We show that the least-squares estimate method in general behaves differently for interval type-2 ANFIS models compared to type-1 ANFIS models, producing larger errors for interval type-2 ANFIS.}, conference = {2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2016)}, organization = {Vancouver, Canada}, publicationstatus = {Published}, url = {https://nottingham-repository.worktribe.com/output/798428}, year = {2016}, author = {Chen, Chao and John, Robert and Twycross, Jamie and Garibaldi, Jonathan M.} }