Application of PSO (particle swarm optimization) and GA (genetic algorithm) techniques on demand estimation of oil in Iran

• Published in: Energy (Oxford) Vol. 35; no. 12; pp. 5223 - 5229
• Main Authors: Assareh, E., Behrang, M.A., Assari, M.R., Ghanbarzadeh, A.
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier Ltd 01.12.2010; Elsevier
• Subjects: Applied sciences; Demand; Domestic; Economic data; Energy; Energy economics; Estimates; Exact sciences and technology; Exports; Fossil fuels and derived products; GA (genetic algorithm); General, economic and professional studies; Genetic algorithms; Marketing; Mathematical models; Methodology. Modelling; Oil; Optimization; Projection; PSO (particle swarm optimization); Iran; Asia; Demand; PSO (particle swarm optimization); Projection; Oil; GA (genetic algorithm); Genetic algorithm; Socioeconomic study; Long term; Modeling; Particle swarm optimization; Forecasting; Petroleum

This paper presents application of PSO (Particle Swarm Optimization) and GA (Genetic Algorithm) techniques to estimate oil demand in Iran, based on socio-economic indicators. The models are developed in two forms (exponential and linear) and applied to forecast oil demand in Iran. PSO–DEM and GA–DEM...