The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON ENVIRONMENT AND DEVELOPMENT
Transactions ID Number: 89-386
Full Name: Omer Faruk Cansiz
Position: Please, select:
Age: ON
Sex: Male
Address: Department of Civil Engineering, Faculty of Engineering, Mustafa Kemal University., Iskenderun, 31200 Hatay, Turkey
Country: TURKEY
Tel: 3266135613-4225
Tel prefix: +90
Fax:
E-mail address: ofcansiz@mku.edu.tr
Other E-mails: ofcansiz@hotmail.com
Title of the Paper: Energy Intensity Forecasting Model Using Activity Share of Highways and Railways in Turkey
Authors as they appear in the Paper: Omer Faruk Cansiz
Email addresses of all the authors: ofcansiz@mku.edu.tr
Number of paper pages: 14
Abstract: The modal share of highways transportation in Turkey has very high value opposite to railway transportation. The energy consumed on highways transportation per ton-km (tkm) or passenger-km (pkm) is much higher than railway transportation. In Turkey, during the 1988-2005 periods, it was observed that energy intensity on highways transportation was decreased remarkably. However, the activity share of highways increased during this period. Although, the modal share of activity on railways transportation was shown declining tendency, the energy intensity of railways was showing increasing propensity. In this study, the ANN model was built to take advantage of the relationship between modal activity share and modal energy intensity in transport of Turkey. ANN model is constructed by using the modal share of freight on highways, the modal share of passenger transportation of highways, the modal share of freight on railways and the modal share of passenger transportation !
on railways are used as inputs and the energy intensity of freight on highways, the energy intensity of passenger transportation on highways, the energy intensity of freight on railways, the energy intensity of passenger transportation on railways as outputs variables. The best ANN model for the estimation of energy intensity has 0,9844, 0,0157 and 5,59%, Rsquare, mean square error and average percent error, respectively. The explicit mathematical formulation of this ANN model is formed by using optimum weights and bias. The ANN model reflected the fluctuations in the data set to the predicted values. The proposed ANN model can be used to develop energy efficiency scenarios, which can be performed by changing modal activity share.
Keywords: Energy Intensity; Modal Activity Share; Artificial neural network; Energy Efficiency
EXTENSION of the file: .doc
Special (Invited) Session: An Energy Analysis of Road Transportation in Turkey
Organizer of the Session: 101-169
How Did you learn about congress: 1.Assoc.Prof. Ahmet Oztas---aoztas@gantep.edu.tr,2.Asst.Prof. Erdoðan Ozbay---ozbay@gantep.edu.tr,3.Assoc.Prof. Ozgur Kisi---kisi@erciyes.edu.tr
IP ADDRESS: 88.249.53.41
