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:: Volume 19, Number 4 (1-2017) ::
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Modeling and prediction of natural gas consumption with help of multi objective GMDH-Type Neural Network. Case study: regional gas distribution company of Rasht city.
Allahyar Daghbandan *, Nesa Setayesh2
Proffessor Guilan university, Guilan-Rasht-Guilan universiti-Dept. of Eng. - , daghbandan@guilan.ac.ir
2- Guilan-Rasht-Guilan universiti-Dept. of Eng.
Abstract:   (20 Views)

ABSTRACT

It is widely accepted that natural gas is a clean energy source that can be used to meet energy demand for heating and industrial purposes among the fossil fuels and its usage remarkably increases in order to maintain a clean environment in many countries in the world. In this paper, factors affecting gas consumption were firstly identified and then GMDH-Type Neural Networks has been used for modeling and prediction of gas consumption using input-output data set. To validate the proposed model, a case study was carried out based on the data consisted of 84 sets for 7 years obtained from regional gas distribution company of Rasht city. For modeling, the experimental data were divided into train and test sections (70% for training and 30% for testing). The predicted values were compared with those of experimental values . The GMDH-Type Neural Network model values showed a very good regression with the experimental results and the Coefficient of determination was obtained 0.8943.

Keywords: Gas consumption, GMDH-NN, Modeling, Prediction.
Full-Text [PDF 341 kb]   (15 Downloads)    
Type of Study: Research | Subject: Energy Planning Models
Received: 2015/03/1 | Accepted: 2015/09/30 | Published: 2017/07/17
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Daghbandan A, Setayesh N. Modeling and prediction of natural gas consumption with help of multi objective GMDH-Type Neural Network. Case study: regional gas distribution company of Rasht city.. 3. 2017; 19 (4)
URL: http://necjournals.ir/article-1-831-en.html
Volume 19, Number 4 (1-2017) Back to browse issues page
نشریه انرژی ایران Iranian Journal of Energy
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