Determining significant parameters in the design of ANFIS

Adaptive Neuro-Fuzzy Inference System (ANFIS) has become a popular tool in neuro-fuzzy modeling. However, since it includes many parameters needed to be set, its designing process is a complicated and time-intensive task for experimenters. To tackle this problem, in this paper we implement the Design of Experiment (DOE) technique to identify the significant parameters of ANFIS when it applies to the problem of stock price prediction. Using full factorial design, nine factors are considered as independent variables. Results identify six factors as statistically significant parameters, as well as four significant interactions between some independent variables.