Oil Consumption Forecasting in Turkey using Artificial Neural Network

Ebru Turanoglu, Ö. Senvar, C. Kahraman
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引用次数: 6

Abstract

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.
基于人工神经网络的土耳其石油消费预测
过去30年,石油和能源市场经历了巨大变化。由于这些变化,用回归等传统方法对石油消耗进行建模和预测可能会很困难。人工神经网络是回归预测和时间序列预测的有力对手。人工神经网络为决策者提供了良好的准确性和更可靠、更精确的预测,在这方面,人工神经网络可以通过提供良好的模型结果为石油消耗管理奠定基础。本文试图通过土耳其1965年至2010年的人口、GDP、进出口数据等预定输入,利用人工神经网络展开土耳其石油消费预测,旨在找到数据的本质结构,以更小的误差预测土耳其未来的石油消费。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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