Oil Consumption Forecasting in Turkey using Artificial Neural Network

被引：5

作者：

Turanoglu, Ebru ^{[1
]}

Senvar, Ozlem ^{[2
]}

Kahraman, Cengiz ^{[3
]}

机构：

[1] Izmir Univ, Dept Ind Engn, Izmir, Turkey

[2] Marmara Univ, Dept Ind Engn, Ind Engn, Istanbul, Turkey

[3] Istanbul Tech Univ, Dept Ind Engn, Istanbul, Turkey

来源：

INTERNATIONAL JOURNAL OF ENERGY OPTIMIZATION AND ENGINEERING | 2012年 / 1卷 / 04期

关键词：

Artificial Neural Network (ANN); Forecasting; Least-Squares Method; Oil Consumption; Regression;

D O I：

10.4018/ijeoe.2012100106

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

Oil and energy markets have experienced dramatic changes over the past three decades. Due to these changes, it may be difficult to model and forecast the oil consumption with traditional methods such as regression. Artificial Neural Networks (ANNs) are the strong rival of regression and time series in forecasting. ANNs provide good accuracy along with more reliable and precise forecasting for policy makers, in this regard, ANNs can establish the foundation for oil consumption management by providing good model results. This paper tries to unfold the oil consumption forecasting in Turkey using ANN through some predetermined inputs, which is data for population, GDP, import and export of Turkey from 1965 to 2010, with the aim of finding the essential structure of the data to forecast future oil consumption in Turkey with less error.

引用

页码：89 / 105

页数：17

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