Crude Palm Oil Price Forecasting: Comparative Study of Hybrid GMDH Neural Network and ARIMA Model
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-16-8903-1_27
Reference43 articles.
1. D Chalil R Barus 2018 The sustainability of Indonesia Pakistan palm oil supply chain J. Manaj. Dan Agribisnis. 15 136 142 https://doi.org/10.17358/jma.15.2.136
2. MK Lam KT Tan KT Lee AR Mohamed 2009 Malaysian palm oil: surviving the food versus fuel dispute for a sustainable future Renew. Sustain. Energy Rev. 13 1456 1464 https://doi.org/10.1016/j.rser.2008.09.009
3. MH Ahmad PY Ping N Mahamed 2014 Volatility modelling and forecasting of Malaysian crude palm oil prices Appl. Math. Sci. 8 6159 6169 https://doi.org/10.12988/ams.2014.48650
4. A.L. Mohamad Hanapi, M. Othman, R. Sokkalingam, H. Sakidin, Developed a hybrid sliding window and GARCH model for forecasting of crude palm oil prices in Malaysia. J. Phys. Conf. Ser. 1123 (2018). https://doi.org/10.1088/1742-6596/1123/1/012029
5. A. Bin Khamis, R. Hameed, M.E. Nor, N. Che Him, R. Mohd Salleh, S.N.A. Mohd Razali, Comparative Study on Forecasting Crude Palm Oil Price using Time Series Models, Sci. Res. J. VI (2018). doi:https://doi.org/10.31364/scirj/v6.i12.2018.p1218588
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