Genetic algorithm (GA) approaches for the transport energy demand estimation: Model development and application


Canyurt O. E., Ozturk H. K., Hepbasli A., Utlu Z.

ENERGY SOURCES PART A-RECOVERY UTILIZATION AND ENVIRONMENTAL EFFECTS, vol.28, no.15, pp.1405-1413, 2006 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 28 Issue: 15
  • Publication Date: 2006
  • Doi Number: 10.1080/15567030600917033
  • Journal Name: ENERGY SOURCES PART A-RECOVERY UTILIZATION AND ENVIRONMENTAL EFFECTS
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.1405-1413
  • Keywords: genetic algorithm, GA, energy, energy planning, energy modeling, energy policy, future projections, transportation, Turkey, OPTIMIZATION, DESIGN, CANADA, SYSTEM
  • Gazi University Affiliated: No

Abstract

This study deals with estimating future transport energy demand using genetic algorithm (GA) approach. Genetic algorithm transport energy demand (GATENDM) model is developed based on socio-economic indicators (population, gross domestic product (GDP), import and export) and transportation indicators/parameters (car, bus, and truck sales). The GATENDM model developed is applied to Turkey, which is selected as an application country. This model in a quadratic form was found to provide the best fit solution to the observed data. It may be concluded that the model proposed can be used as an alternative solution and estimation technique to available estimation technique in predicting the future transportation energy utilization values of countries.