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Forecasting natural gas consumption in Istanbul using neural networks and multivariate time series methods

Title	Forecasting natural gas consumption in Istanbul using neural networks and multivariate time series methods
Author	Demirel, Ö. F., Zaim, S., Çalışkan, A., Özuyar, Pınar Gökçin
Publication Date:	2012
Publication Place	- TÜBİTAK
Subject	Forecasting, Neural networks, Natural gas, Time series
Type	Periodical
Language	English
Digital	Yes
Manuscript	No
Library:	Özyeğin University
Library Asset ID	1303-6203
Record ID	51631f67-ff4c-41b4-b445-d3ddf14b813f
Library Location	Entrepreneurship
Date	2012
Sample Text	The fast changes and developments in the world's economy have substantially increased energy consumption. Consequently, energy planning has become more critical and important. Forecasting is one of the main tools utilized in energy planning. Recently developed computational techniques such as genetic algorithms have led to easily produced and accurate forecasts. In this paper, a natural gas consumption forecasting methodology is developed and implemented with state-of-the-art techniques. We show that our forecasts are quite close to real consumption values. Accurate forecasting of natural gas consumption is extremely critical as the majority of purchasing agreements made are based on predictions. As a result, if the forecasts are not done correctly, either unused natural gas amounts must be paid or there will be shortages of natural gas in the planning periods.
DOI	10.3906/elk-1101-1029
Cilt	20

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Özyeğin University

Forecasting natural gas consumption in Istanbul using neural networks and multivariate time series methods

Author Demirel, Ö. F., Zaim, S., Çalışkan, A., Özuyar, Pınar Gökçin

Publication Date 2012

Publication Place - TÜBİTAK

Subject Forecasting, Neural networks, Natural gas, Time series

Type Periodical

Language English

Digital Yes

Manuscript No

Library Özyeğin University

Library Asset ID 1303-6203

Record ID 51631f67-ff4c-41b4-b445-d3ddf14b813f

Library Location Entrepreneurship

Date 2012

Sample Text The fast changes and developments in the world's economy have substantially increased energy consumption. Consequently, energy planning has become more critical and important. Forecasting is one of the main tools utilized in energy planning. Recently developed computational techniques such as genetic algorithms have led to easily produced and accurate forecasts. In this paper, a natural gas consumption forecasting methodology is developed and implemented with state-of-the-art techniques. We show that our forecasts are quite close to real consumption values. Accurate forecasting of natural gas consumption is extremely critical as the majority of purchasing agreements made are based on predictions. As a result, if the forecasts are not done correctly, either unused natural gas amounts must be paid or there will be shortages of natural gas in the planning periods.

DOI 10.3906/elk-1101-1029

Cilt 20