| Research Article: | Forecasting Retail Oil and Natural Gas Vehicles Prices in Thailand Using Time Series Data Mining Techniques |
| Author: | Pitchayakorn Lake |
| Email: | pitchayakorn@siam.edu |
| Department|Faculty: | Department of Digital Business, Faculty of Information Technology, Siam University, Bangkok 10160 |
| Published | Journal of Positive School Psychology, Volume 6, No. 3, 23 March 23, 2022, pages 9537-9541 |
Citation
Lake P. (2022). Forecasting retail oil and natural gas vehicles prices in Thailand using time series data mining techniques. Journal of Positive School Psychology, 6(3), 9537-9541.
ABSTRACT
The purpose of this research is to develop the model of forecasting retail oil and natural gas vehicles prices for automobiles in Thailand using time series data mining techniques. There are three techniques such as Linear Regression, Multi-Layer Perceptron and Support Vector Machine for Regression. The data used for this study was collected the retail oil and natural gas vehicles prices in Thailand from 2012-2018 AD. totally 84 months. This research found that the suitable forecasting model for retail oil and natural gas vehicles prices as followed: 1) The forecasting model using Linear Regression was the most suitable for Gasohol E85 and Ultra Force Diesel, which had the rate of MMRE (Mean Magnitude of Relative Error) with the percentage of 2.46, and 4.60. 2) The forecasting model using Support Vector Machine for Regression was the most suitable for Gasohol 91, Gasohol 95, Gasohol E20 and Natural Gas Vehicles (NGV), which had the rate of MMRE with the percentage of 3.69, 3.20, 3.54, and 6.89, respectively.
Keywords: Retail Oil and Natural Gas Vehicles Prices in Thailand, Times Series Analysis, Data Mining Techniques
Forecasting Retail Oil and Natural Gas Vehicles Prices in Thailand Using Time Series Data Mining Techniques
Faculty of Information Technology, Siam University, Bangkok, Thailand