Adaptive neuro-fuzzy inference system for combined forecasts in a panel manufacturer

作者：Wang Fu Kwun^*; Chang Ku Kuang

来源：Expert Systems with Applications, 2010, 37(12): 8119-8126.

DOI：10.1016/j.eswa.2010.05.076

• Demand forecasting
• Combined forecasts
• Fuzzy neural network
• Adaptive neuro-fuzzy inference system

Improving the accuracy of demand forecasting has become a primary concern for a thin-film transistor liquid crystal display manufacturer. To address this concern, we develop a demand forecasting methodology that combines market and shipment forecasts. We investigate the weights assigned to the combination of forecasts using three linear methods (the minimum values of the forecast error, the adaptive weights and the regression analysis), as well as two nonlinear methods (fuzzy neural network and adaptive network based fuzzy inference system). A real data set from a panel manufacturer in Taiwan is used to demonstrate the application of the proposed methodology. The results show that the adaptive network based fuzzy inference system method outperforms other four methods. Also, we find that the mean absolute percent error (MAPE) of forecasting accuracy using the adaptive network based fuzzy inference system method can be improved effectively.

• 出版日期2010-12