Mojtaba Abbasian; Ali Sardar Shahraki; Javad shahraki
Abstract
Energy plays a significant role in today's developing societies. The role of energy demands to make decisions and policy with regard to its production, distribution, and supply. The vital importance of energy, especially fossil fuels, is a factor affecting agricultural production. This factor has a great ...
Read More
Energy plays a significant role in today's developing societies. The role of energy demands to make decisions and policy with regard to its production, distribution, and supply. The vital importance of energy, especially fossil fuels, is a factor affecting agricultural production. This factor has a great influence on the production of agricultural products in Iran. The forecast of the consumption of oil products by the agricultural sector can help managers and planners to adopt sound management practices for their consumption. Presently, artificial neural networks are regarded as a powerful tool for the analysis and modeling of nonlinear relationships. The present study employed GMDH and RBF artificial neural networks to estimate the consumption of oil products by the agricultural sector. The underpinning parameters were selected to include the value added to the fixed price, rural population, agricultural land area, agricultural mechanization (tractor), and the consumption rate of oil products, electricity, price of oil products, and total energy use by the agricultural sector for the period of 1967-2017. The comparison of MSE, MAE, and MAPE for the GMDH and RBF models showed that the GMDH neural network was highly capable of modeling the energy consumption of the agricultural sector.
Mohammad Ali Feizpour; Mohammad Khayyat Sarkar
Abstract
Although the implementation of targeted energy subsidies plan has been considered by policymakers since the First 5-year Economic, Social and Cultural Development Plan in Iran, it is only partially implemented in 2010. This issue has great importance for industry sector that has benefited from subsidized ...
Read More
Although the implementation of targeted energy subsidies plan has been considered by policymakers since the First 5-year Economic, Social and Cultural Development Plan in Iran, it is only partially implemented in 2010. This issue has great importance for industry sector that has benefited from subsidized energy prices. This research attempts to investigate the possible impact of implementing Subsidy Reform Plan on manufacture of non-metal mineral products industry by using Artificial Neural Network approach. This investigation focuses on new entered firms into this industry as one of the most energy intensive industries. The results indicate that by replacing subsidized prices with electricity real price, the consumption of this energy carrier will generally decline by 16 percent. Despite this, the large entrance of new firms has raised the energy consumption in some years. Therefore, the results show that targeted subsidies plan does not have a large impact on energy consumption in non-metal mineral manufacturing industries. Furthermore, we find out that the impact of this policy depends on combination of firms in each industry.
