An adaptive neuro fuzzy inference system for prediction of anxiety of students

Abstract

In this paper authors propose design methodology and application of Adaptive Neuro-Fuzzy Inference System (ANFIS) in prediction of anxiety of students using hybrid learning algorithm to improve the prediction based on the conventional model using questioner. Here, first order Sugeno fuzzy model considered whose parameters are tuned through hybrid learning algorithm. The performance of proposed model is verified in terms of the prediction errors. It is found that both Mean Absolute Percentage Error (MAPE) and Root Mean Square Error (RMSE) are reduced significantly. The results establish that fusion of fuzzy logic and neural network with hybrid learning algorithm can be very useful in Psychological research.