Neuro fuzzy model with singular value decomposition for forecasting the number of train passengers in Yogyakarta

The neuro fuzzy model is a model that combines fuzzy and neural network, which has been applied to time series forecasting. A singular value decomposition method can be utilized for optimization of the neuro-fuzzy model based on the singular values of the matrix. This research aims to forecast the number of train passengers of PT Kereta Api Indonesia (Persero) Operating Region VI Yogyakarta by applying the neuro-fuzzy model with singular value decomposition. The forecasting accuracy of the proposed model is compared with those of the one order Takagi Sugeno Kang fuzzy model and the neuro-fuzzy whose optimization is done by the least square method. The results demonstrate that neuro-fuzzy models with singular value decomposition are more accurate than the other two models on testing data but not better on training data.