2004
DOI: 10.1080/00908310490441610
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Energy Demand Estimation Based on Two-Different Genetic Algorithm Approaches

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Cited by 63 publications
(28 citation statements)
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“…Their forecasting model adopted genetic algorithm and estimated energy demand better than the government's model. Canyurt et al [41] modeled Turkey's future energy demand using the genetic algorithm approach based on GDP, population, and import and export figures. Sozen et al [9] also used ANN to forecast Turkey's net energy consumption.…”
Section: Literature Reviewmentioning
confidence: 99%
“…Their forecasting model adopted genetic algorithm and estimated energy demand better than the government's model. Canyurt et al [41] modeled Turkey's future energy demand using the genetic algorithm approach based on GDP, population, and import and export figures. Sozen et al [9] also used ANN to forecast Turkey's net energy consumption.…”
Section: Literature Reviewmentioning
confidence: 99%
“…Ediger and Tatlıdil [5] applied cyclic pattern method for forecasting primary energy demand in Turkey. Canyurt et al [6] modelled Turkey's future energy demand using genetic algorithm approach based on gross domestic product, population, import and export figures. Ozturk and Ceylan [7] utilized from genetic algorithm to forecast electricity demand for Turkey based on socio-economic indicators.…”
Section: Introductionmentioning
confidence: 99%
“…Taylor and Majithia (2000) have made combined forecasts in accordance with varying weights by taking into account three popular traditional methods. Ceylan et al (2005), Canyurt et al (2004Canyurt et al ( , 2008, and Ozturk et al (2006) proposes different models based on genetic algorithms for estimating energy and exergy demand in their studies. Ozcelik and Hepbasli (2006) have used a simulated annealing approach for estimating petroleum exergy production and consumption.…”
Section: Literature Reviewmentioning
confidence: 99%