Please use this identifier to cite or link to this item: https://hdl.handle.net/11499/4880
Title: Estimating energy and exergy production and consumption values using three different genetic algorithm approaches. Part 1: Model development
Authors: Ceylan, H.
Ozturk, H.K.
Hepbasli, A.
Utlu, Z.
Keywords: Energy
Energy demand
Energy modeling
Energy planning
Exergy
Exergy modeling
Future projections
GA
Genetic algorithm
Economic and social effects
Energy utilization
Error analysis
Fossil fuels
Mathematical models
Planning
Exergy exergy modeling
Genetic algorithms
Abstract: The present study, consisting of two parts, proposes new models for estimating energy and exergy production and consumption values using the genetic algorithm approach. Part 1 of this study deals with the model development, while the application and testing with various scenarios will be treated in Part 2. In this regard, the genetic algorithm energy (GAEN) and genetic algorithm exergy (GAEX) estimating models have been proposed. During the energy and exergy estimation, independent variables are the GDP, population, and the ratio of export to import. The three forms of the GAEN and GAEX are developed, of which one is linear, second is exponential and the third is a mix of the exponential and linear form of the equations. Among them, the best fit models in terms of average relative errors and for the testing period are selected for future estimation and proposed both for GAEN and GAEX. It may be concluded that the models proposed here can be used as an alternative solution and estimation techniques to available estimation techniques. Copyright © Taylor & Francis inc.
URI: https://hdl.handle.net/11499/4880
https://doi.org/10.1080/00908310490448604
ISSN: 0090-8312
Appears in Collections:Mühendislik Fakültesi Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

Show full item record



CORE Recommender

SCOPUSTM   
Citations

8
checked on Oct 13, 2024

WEB OF SCIENCETM
Citations

9
checked on Nov 16, 2024

Page view(s)

40
checked on Aug 24, 2024

Google ScholarTM

Check




Altmetric


Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.