Forecasting Iran’s Energy Demand Using Cuckoo Optimization Algorithm

Sayyed Abdolmajid Jalaee, Amin GhasemiNejad, Mehrdad Lashkary and Maryam Rezaee Jafari

Mathematical Problems in Engineering, 2019, vol. 2019, 1-8

Abstract:

This study deals with the modeling of the energy consumption in Iran to forecast future projections based on socioeconomic and demographic variables (GDP, population, import and export amounts, and employment) using the cuckoo optimization algorithm. For this purpose, four diverse models including different indicators were used in the analyses. Linear and power forms of equations are developed for each model. The related data between 1972 and 2013 were used, partly for installing the models. The result of the models shows that the obtained demand estimation linear models are in closer agreement with the observed data, particularly the linear model with five independent variables including GDP, population, import, export, and employment, which outperformed other linear models. Finally, the future energy demand of Iran is forecasted up to the year 2030 using these models under three scenarios.

Date: 2019
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://downloads.hindawi.com/journals/MPE/2019/2041756.pdf (application/pdf)
http://downloads.hindawi.com/journals/MPE/2019/2041756.xml (text/xml)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:2041756

DOI: 10.1155/2019/2041756

Access Statistics for this article

More articles in Mathematical Problems in Engineering from Hindawi
Bibliographic data for series maintained by Mohamed Abdelhakeem ().