COMPARISON OF SOME STATISTICAL FORECASTING TECHNIQUES WITH GMDH PREDICTOR: A CASE STUDY

Authors

  • Syed Misbah Uddin Industrial and Production Engineering Department, ShahJalal University of Science and Technology, Sylhet, Bangladesh.
  • Aminur Rahman Industrial and Production Engineering Department, ShahJalal University of Science and Technology, Sylhet, Bangladesh.
  • Emtiaz Uddin Ansari Industrial and Production Engineering Department, ShahJalal University of Science and Technology, Sylhet, Bangladesh.

DOI:

https://doi.org/10.3329/jme.v47i1.35354

Abstract

Demand forecasts are extremely important for manufacturing industry and also needed for all type of business and business suppliers for distribution of finish products to the consumer on time. This study is concerned with the determination of accurate models for forecasting cement demand. In this connection this paper presents results obtained by using a self-organizing model and compares them with those obtained by usual statistical techniques. For this purpose, Monthly sales data of a typical cement ranging from January, 2007 to February, 2016 were collected. A nonlinear modelling technique based on Group Method of Data Handling (GMDH) is considered here to derive forecasts. Forecast were also made by using various time series smoothing techniques such as exponential smoothing, double exponential smoothing, moving average, weightage moving average and regression method. The actual data were compared to the forecast generated by the time series model and GMDH model. The mean absolute deviation (MAD, mean absolute percentage error (MAPE) and mean square error (MSE) were also calculated for comparing the forecasting accuracy. The comparison of modelling results shows that the GMDH model perform better than other statistical models based on terms of mean absolute deviation (MAD), mean absolute percentage error (MAPE) and mean square error (MSE).

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Published

2018-05-01

How to Cite

Uddin, S. M., Rahman, A., & Ansari, E. U. (2018). COMPARISON OF SOME STATISTICAL FORECASTING TECHNIQUES WITH GMDH PREDICTOR: A CASE STUDY. Journal of Mechanical Engineering, 47(1), 16–21. https://doi.org/10.3329/jme.v47i1.35354

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Articles