A Novel Chicken Swarm Neural Network Model for Crude Oil Price Prediction

Author(s):  
Abdullah Khan ◽  
Rahmat Shah ◽  
Junaid Bukhari ◽  
Nasreen Akhter ◽  
Attaullah ◽  
...  
2016 ◽  
Vol 10 (2) ◽  
pp. 71-77 ◽  
Author(s):  
Mohammad Reza Mahdiani ◽  
Ehsan Khamehchi

2021 ◽  
pp. 321-326
Author(s):  
Sivaprakash J. ◽  
Manu K. S.

In the advanced global economy, crude oil is a commodity that plays a major role in every economy. As Crude oil is highly traded commodity it is essential for the investors, analysts, economists to forecast the future spot price of the crude oil appropriately. In the last year the crude oil faced a historic fall during the pandemic and reached all time low, but will this situation last? There was analysis such as fundamental analysis, technical analysis and time series analyses which were carried out for predicting the movement of the oil prices but the accuracy in such prediction is still a question. Thus, it is necessary to identify better methods to forecast the crude oil prices. This study is an empirical study to forecast crude oil prices using the neural networks. This study consists of 13 input variables with one target variable. The data are divided in the ratio 70:30. The 70% data is used for training the network and 30% is used for testing. The feed forward and back propagation algorithm are used to predict the crude oil price. The neural network proved to be efficient in forecasting in the modern era. A simple neural network performs better than the time series models. The study found that back propagation algorithm performs better while predicting the crude oil price. Hence, ANN can be used by the investors, forecasters and for future researchers.


2012 ◽  
Vol 6 (1) ◽  
pp. 31-41 ◽  
Author(s):  
A. Naseri ◽  
S. H. Yousefi ◽  
A. Sanaei ◽  
A. A. Gharesheikhlou

Author(s):  
Somboon Chuaykoblap ◽  
Parames Chutima ◽  
Achara Chandrachai ◽  
Natawut Nupairoj

Sign in / Sign up

Export Citation Format

Share Document