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The Estimation of Vehicle Ownership via Flower Pollination Algorithm in Turkey

Year 2018, Volume: 4 Issue: 1, 39 - 45, 29.04.2018

Abstract

In this study, vehicle ownership in
Turkey is modeled using a new meta-heuristic optimization technique and
projection  are executed for the future.
The models that estimate the number of vehicles per 1000 people has been
developed via the Flower Pollution Algorithm (FPA) which is one of the most
recent and most popular optimization methods in recent years, While the models
were being developed, linear and force forms were proposed using 3 independent
parameters. For the input parameters of the models, the License Number (LS) between
2004 and 2016, the Domestic Product per Capita (GNP) as dollars and fuel prices
(as gasoline, diesel and LPG) were used. The coefficients of the two models
were optimized by FPA and models were created to obtain the number of vehicle
for each fuel consumption. The sum of number of vehicle according to fuel types
shows the vehicle ownership in Turkey and the performances of the models have
been evaluated statistically. The statistical results have showed that the FPA
approach demonstrated its usefulness in vehicle ownership by showing an
efficient and successful performance. In parallel with the increase in
stability and welfare in Turkey, it is estimated that the number of vehicles
will continue to increase rapidly and will increase by about 30% in 2025. 

References

  • [1] Tanner J.C. 1958. An Analysis of Increases in Motor Vehicles in Great Britain. Research Note RN/1631, Road Research Laboratory.
  • [2] Tanner J.C. 1975. Forecasts of Vehicles and Traffic in Great Britain: 1974 Revision. Transport and Road Research Laboratory Report LR 650.
  • [3] Button K., Ngoe N. and Hine J. 1993. Modelling Vehicle Ownership and Use in Low Income Countries, Journal of Transport Economics and Policy, 51-67.
  • [4] Dargay J., Gately D., and Sommer M. 2007. Vehicle Ownership and Income Growth, Worldwide: 1960-2030, The Energy Journal, 28(4), 143-171.
  • [5] Chingcoanco F. and Miller E. J. 2014. A Meta-model of Vehicle Ownership Choice Parameters. Transportation, 2014, 41, 923-945. [6] Anowar S., Eluru N., and Miranda-Moreno L. F. 2016. Analysis of Vehicle Ownership Evolution in Montreal, Canada using Pseudo Panel Analysis. Transportation, 43, 531-548.
  • [7] Liu Y. and Cirillo C. 2016. Small Area Estimation of Vehicle Ownership and Use. Transportation Research Part D, 47, 136-148.
  • [8] Choudhary R. and Vasudevan V. 2017. Study of vehicle ownership for urban and rural households in India. Journal of Transport Geography, 58, 52-58.
  • [9] Ogut K. S. 2006. Modelling Car Ownership in Turkey using Fuzzy Regression. Transportation Planning and Technology, 29(3), 233-248.
  • [10] Çodur M. Y. and Tortum A. 2009. Modelling Car Ownership in Turkey using Neural Network. Proceedings of the Institution of Civil Engineers, issue TR2, 97-106.
  • [11] Korkmaz E., Akgungor A. P. and Dogan E. 2016. Estimation of Car Ownership in Turkey using Artificial Bee Colony Algorithm”, In:Proceedings of the Third International Conference on Traffic and Transport Engineering. Belgrad, Serbia: IJTTE, 563-569.
  • [12] Yang X.-S. 2014. Nature-inspired optimization algorithms. Elsevier.
  • [13] İnternet: Turkish Statistical Institute Road Traffic Accident Statistics, 1994-2015. http://www.tuik.gov.tr

Türkiye'deki Araç Sahipliğinin Çiçek Tozlaşma Algoritması ile Tahmini

Year 2018, Volume: 4 Issue: 1, 39 - 45, 29.04.2018

Abstract

Bu çalışmada yeni bir meta
sezgisel optimizasyon tekniği kullanılarak Türkiye’deki araç sahipliği
modellenmiş ve geleceğe yönelik tahminler yapılmıştır. Son zamanların en güncel
ve en popüler optimizasyon yöntemlerinden birisi olan Çiçek Tozlaşma
Algoritması (ÇTA) ile 1000 kişi başına düşen araç sayısını tahmin eden modeller
geliştirilmiştir. Modeller geliştirilirken, 3 bağımsız parametre kullanılarak,
doğrusal ve kuvvet formlarında modeller önerilmiştir. Modellerin girdi
parametreleri için 2004 ile 2016 yılları arasındaki Ehliyet sayısı (ES), dolar
bazında Kişi Başına Düşen Gayri Safhi Milli Hasıla (GSMH) ve yakıt fiyatları
(benzin, dizel ve lpg olarak) kullanılmıştır. Ortaya konan iki modelin
katsayıları ÇTA ile optimize edilerek belirlenmiş ve her bir yakıt tüketimi
için araç sayılarını veren modeller kurulmuştur. Yakıt türlerine göre araç
sayılarının toplamı, Türkiye’deki araç sahipliğini göstermekte olup, modellerin
performansları istatistiksel olarak değerlendirilmiştir. İstatistiki sonuçlar
ÇTA yaklaşımının etkin ve başarılı bir performans göstererek araç sahipliğinde
kullanılabilirliğini ortaya koymuştur. Ayrıca Türkiye’deki istikrar ve refah
düzeyinin artışına paralel olarak, araç sayısının hızla artmaya devam edeceği
ve 2025 yılında yaklaşık %30 artacağı tahmin edilmiştir.

References

  • [1] Tanner J.C. 1958. An Analysis of Increases in Motor Vehicles in Great Britain. Research Note RN/1631, Road Research Laboratory.
  • [2] Tanner J.C. 1975. Forecasts of Vehicles and Traffic in Great Britain: 1974 Revision. Transport and Road Research Laboratory Report LR 650.
  • [3] Button K., Ngoe N. and Hine J. 1993. Modelling Vehicle Ownership and Use in Low Income Countries, Journal of Transport Economics and Policy, 51-67.
  • [4] Dargay J., Gately D., and Sommer M. 2007. Vehicle Ownership and Income Growth, Worldwide: 1960-2030, The Energy Journal, 28(4), 143-171.
  • [5] Chingcoanco F. and Miller E. J. 2014. A Meta-model of Vehicle Ownership Choice Parameters. Transportation, 2014, 41, 923-945. [6] Anowar S., Eluru N., and Miranda-Moreno L. F. 2016. Analysis of Vehicle Ownership Evolution in Montreal, Canada using Pseudo Panel Analysis. Transportation, 43, 531-548.
  • [7] Liu Y. and Cirillo C. 2016. Small Area Estimation of Vehicle Ownership and Use. Transportation Research Part D, 47, 136-148.
  • [8] Choudhary R. and Vasudevan V. 2017. Study of vehicle ownership for urban and rural households in India. Journal of Transport Geography, 58, 52-58.
  • [9] Ogut K. S. 2006. Modelling Car Ownership in Turkey using Fuzzy Regression. Transportation Planning and Technology, 29(3), 233-248.
  • [10] Çodur M. Y. and Tortum A. 2009. Modelling Car Ownership in Turkey using Neural Network. Proceedings of the Institution of Civil Engineers, issue TR2, 97-106.
  • [11] Korkmaz E., Akgungor A. P. and Dogan E. 2016. Estimation of Car Ownership in Turkey using Artificial Bee Colony Algorithm”, In:Proceedings of the Third International Conference on Traffic and Transport Engineering. Belgrad, Serbia: IJTTE, 563-569.
  • [12] Yang X.-S. 2014. Nature-inspired optimization algorithms. Elsevier.
  • [13] İnternet: Turkish Statistical Institute Road Traffic Accident Statistics, 1994-2015. http://www.tuik.gov.tr
There are 12 citations in total.

Details

Primary Language Turkish
Subjects Civil Engineering
Journal Section Articles
Authors

Ersin Korkmaz

Ali Payidar Akgüngör This is me

Publication Date April 29, 2018
Submission Date January 18, 2018
Acceptance Date March 10, 2018
Published in Issue Year 2018 Volume: 4 Issue: 1

Cite

IEEE E. Korkmaz and A. P. Akgüngör, “Türkiye’deki Araç Sahipliğinin Çiçek Tozlaşma Algoritması ile Tahmini”, GJES, vol. 4, no. 1, pp. 39–45, 2018.

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