Forecasting Models for Thailand’s Electrical Appliances Export Values

Author:

Banditvilai Somsri1,Klomwises Yuwadee1

Affiliation:

1. Department of Statistics King Mongkut’s Institute of Technology Ladkrabang Bangkok 10520 THAILAND

Abstract

This research aimed to study forecasting models for Thailand’s electrical appliances export values. Thailand’s monthly electrical appliances export values were gathered from the Information Technology and Communication Center, Ministry of Commerce, from January 2006 to November 2022. The data from January 2006 to December 2021 were used to construct and select the forecasting models, and the remaining were used for measuring the model’s accuracy. Since the electrical appliances export values showed trends and seasonal variation, the researcher selected the Holt-Winters method with various initial settings, the Box-Jenkins method, and Long Short-Term Memory Neural Networks (LSTM) for constructing models. The forecasting models were chosen by minimum Root Mean Square Error (RMSE) as a criterion. Mean Absolute Percentage Error (MAPE) was employed to measure the accuracy of the forecasting model. The study revealed that the Box-Jenkins model gave the appropriate forecasting model for Thailand’s electrical appliances export values and gained a MAPE of 8.0%.

Publisher

World Scientific and Engineering Academy and Society (WSEAS)

Subject

Computer Science Applications,Control and Systems Engineering

Reference20 articles.

1. Bank of Ayudhya Research Center, 2021. Business and Industry Trends in Thailand 2021-2023: Electrical Appliance Industry, pp.1-8

2. Bureau of Agricultural and Industrial Trade Promotion, Department of International Trade Promotion, 2021. February monthly report 2021, pp.1-2.

3. A, Segura JV, Bermudez JD. Initial conditions estimations for improving forecast accuracy in exponential smoothing. TOP. Vol 20(2), 2012 Vercher E, Corberan-Vallet pp.517-533.

4. Booranawong T. and Booranawong A., Double exponential smoothing and HoltWinters methods with optimal initial values and weighting factors for forecasting lime, Thai chili, and lemongrass prices in Thailand, Engineering and Applied Science Research, Vol. 45, No. 1, 2018, pp. 32-38.

5. Suppalakpanya, K., Nikhom, R., Booranawong A., Booranawong T., An Evaluation of Holt-Winters Methods with Different Initial Trend Values for Forecasting Crude Palm Oil Production and Prices in Thailand, Suranaree Journal of Science and Technology, Vol. 26, No. 1, 2019, pp. 13-22.

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