Yazar "Canyurt, OE" seçeneğine göre listele
Listeleniyor 1 - 5 / 5
Sayfa Başına Sonuç
Sıralama seçenekleri
Öğe An application of genetic algorithm search techniques to the future total exergy input/output estimation(Taylor & Francis Inc, 2006) Ozturk, HK; Canyurt, OE; Hepbasli, A; Utlu, ZSince 1975, there has been a great deal of interest, particularly during the past decade, in the promising genetic algorithm (GA) and its application to various disciplines from medicine to cogeneration. However, the studies performed on energy-related GA modeling are relatively low in numbers. The main objective of the present study is to develop the exergy input/output estimation equations in order to estimate the future projections based on the GA notion. In this regard, the GA Future Total EXergy Input/Output Estimation Models (GAFTEXIEM/GAFTEXOEM) are used to estimate total exergy input/output demand of Turkey, which is selected as an application country, based on the economic and social indicators of gross domestic product (GDP), population, import, export and house production figures. The future prediction of Turkey's total exergy input/output values are projected between 2003 and 2023. It may be concluded that the models proposed here can be used as an alternative solution and estimation techniques to available estimation techniques. It is also expected that this study will be helpful in developing highly applicable and productive planning for energy policies.Öğe Electricity estimation using genetic algorithm approach: a case study of Turkey(Pergamon-Elsevier Science Ltd, 2005) Ozturk, HK; Ceylan, H; Canyurt, OE; Hepbasli, AThis paper describes the use of stochastic search processes that are the basis of genetic algorithms (GAs), in developing Turkey's electric energy estimation. The industrial sector electricity consumptions and the totals are estimated, based on the basic indicators of the gross national product, population, import and export figures. Two different non-linear estimation models are developed using GA. Developed models are validated with actual data, while future estimation of electricity demand is projected between 2002 and 2025. It may be concluded that the both GAs can possibly be applied to estimate electric energy consumption. (C) 2004 Elsevier Ltd. All rights reserved.Öğe Estimating the Turkish residential-commercial energy output based on genetic algorithm (GA) approaches(Elsevier Sci Ltd, 2005) Canyurt, OE; Ozturk, HK; Hepbasli, A; Utlu, ZThe present study develops three forms of equations to better analyze energy use and make future projections based on genetic algorithm (GA) notion, and examines the effect of the design parameters on the energy utilization values. The models developed in the quadratic form are applied to Turkey, which is selected as an application country. Turkey's future residential energy output demand is estimated based on GDP, population, import, export, house production, cement production and basic house appliances consumption figures. Among these models, the so-called GA-RWTVR model, which uses residential housing production, house appliances sales of washing machine, television, vacuum cleaner and refrigerator as design parameters/indicators, was found to provide the best fit solution to the observed data. It may be concluded that the models proposed can be used as an alternative solution and estimation techniques to available estimation techniques in predicting the future energy utilization values of countries. (C) 2003 Elsevier Ltd. All rights reserved.Öğe Residential-commercial energy input estimation based on genetic algorithm (GA) approaches: an application of Turkey(Elsevier Science Sa, 2004) Ozturk, HK; Canyurt, OE; Hepbasli, A; Utlu, ZThe main objective of the present study is to develop the energy input estimation equations for the residential-commercial sector (RCS) in order to estimate the future projections based on genetic algorithm (GA) notion and to examine the effect of the design parameters on the energy input of the sector. For this purpose, the Turkish RCS is given as an example. The GA Energy Input Estimation Model (GAEIEM) is used to estimate Turkey's future residential-commercial energy input demand based on GDP, population, import, export, house production, cement production and basic house appliances consumption figures. It may be concluded that the three various forms of models proposed here can be used as an alternative solution and estimation techniques to available estimation techniques. It is also expected that this study will be helpful in developing highly applicable and productive planning for energy policies. (C) 2003 Elsevier B.V. All rights reserved.Öğe Three different genetic algorithm approaches to the estimation of residential exergy input/output values(Pergamon-Elsevier Science Ltd, 2004) Ozturk, HK; Canyurt, OE; Hepbasli, A; Utlu, ZThis study develops residential exergy input/output estimation equations in order to better analyze exergy values and predict the future projections using genetic algorithm (GA) notion. GA EXnergy Input/Output Estimation Model (GAEXIEM/GAEXOEM) is used to estimate the future residential exergy input/output values based on the indicators of gross domestic product, population, import, export, house production, cement production and basic house appliances consumption. The model is applied to Turkey's residential sector, of which exergy input and output values were 861.06 and 77.32 PJ in 2002, respectively. The three different estimation models are proposed in quadratic forms. Developed models are validated with actual data, while future estimation of exergy values is projected for the years between 2003 and 2023. It may be concluded that all the models developed seem to be capable of predicting the residential-commercial exergy input/output values of Turkey as well as countries. This study is also expected to give a new direction to engineers, scientists, and policy makers in implementing energy planning studies and in dictating the energy strategies as a potential tool. (C) 2004 Elsevier Ltd. All rights reserved.
