Crude Oil Price Prediction using Artificial Neural Network

被引:28
|
作者
Gupta, Nalini [1 ]
Nigam, Shobhit [1 ]
机构
[1] Pandit Deendayal Petr Univ, Sch Liberal Studies, Gandhinagar, India
关键词
Artificial Neural Network; Crude Oil Price; Prediction Model; Optimal Lag; MODEL;
D O I
10.1016/j.procs.2020.03.136
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Crude oil is amongst the most important resources in today's world, it is the chief fuel and its cost has a direct effect on the global habitat, our economy and oil exploration, exploitation and other activities. Prediction of oil prices has become the need of the hour, it is a boon to many large and small industries, individuals, the government. The evaporative nature of crude oil, its price prediction becomes extremely difficult and it is hard to be precise with the same. Several different factors that affect crude oil prices. We propose a contemporary and innovative method of predicting crude oil prices using the artificial neural network (ANN). The main advantage of this approach of ANN is that it continuously captures the unstable pattern of the crude oil prices which have been incorporated by finding out the optimal lag and number of the delay effect that controls the prices of crude oil. Variation of lag in a period of time has been done for the most optimum and close results, we then have validated our results by evaluating the root mean square error and the results obtained using the proposed model have significantly outperformed. (C) 2020 The Authors. Published by Elsevier B.V.
引用
收藏
页码:642 / 647
页数:6
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