Modified ANFIS architecture - improving efficiency of ANFIS technique

Adaptive neuro-fuzzy inference systems (ANFIS), fusing the capabilities of artificial neural networks and fuzzy inference systems, offer a lot of space for solving different kinds of problems, and are especially efficient in the domain of signal prediction. However, the ANFIS technique is sometimes notated as being computationally expensive. The paper, after considering the conventional ANFIS architecture, brings up a modified ANFIS (MANFIS) structure developed with the intention of making the ANFIS technique more efficient with regard to root mean square error (RMSE) and/or computing time. The standard benchmark, prediction of the Mackey-Glass time series, was used to prove the better performance of the proposed MANFIS structure.