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.
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.. IJE 2017; 19 (4) URL: http://necjournals.ir/article-1-831-en.html