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Designing an innovative model for predicting natural gas consumption in Iranian industries
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Bakhtiar Razani   1, Roya Seifipour2 , Ebrahim Abbasi2 , Bijan Baseri3 |
1- PhD student in Oil and Gas Economics, Islamic Azad University, Central Tehran Branch, Tehran, Iran , br_razani@yahoo.com
2- Assistant Professor, Department of Economics, Islamic Azad University, Central Tehran Branch, Tehran, Iran
3- Assistant Professor, Department of Economics, Islamic Azad University, Central Tehran Branch, Tehran, Iran. |
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Abstract: (167 Views) |
| In order to control the supply and demand of energy and the correct planning in directing the consumption, the monthly gas consumption of the country's industries was investigated with artificial neural network and genetic algorithm in this research for 1402. The country's population information, industrial producer price index, gross domestic product at a fixed price of 90 and gas consumption of the country's industries were investigated as influential variables. The results showed that the best artificial neural network combined with the genetic algorithm is a network with a mutation rate of 0.5, an intersection rate of 0.5, the number of repetitions of 150, and the initial population size of 150. The combination of artificial neural network and genetic algorithm showed that in the spring season there was a total of 2957.7 million barrels of crude oil equivalent, in the summer this figure increased to 3502.6, in the autumn to 4329.9 and in the winter with a growth of 8.15 percent. It will reach 4683 million barrels of crude oil equivalent |
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| Keywords: Prediction, Gas consumption, Artificial neural network, Genetic algorithm |
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Full-Text [PDF 674 kb]
(111 Downloads)
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Type of Study: Research |
Subject:
Management
Received: 2024/12/3 | Accepted: 2024/11/30 | Published: 2024/11/30
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