Article
COMPARATIVE ASSESSMENT OF RADIAL BASIS FUNCTION NEURAL NETWORK AND MULTIPLE LINEAR REGRESSION APPLICATION TO TRIP GENERATION MODELLING IN AKURE, NIGERIA
DOI: 10.7708/ijtte.2019.9(2).03
9 / 2 / 163 - 176 Pages
Author(s)
ETU Japheth Eromietse - Department of Civil Engineering, Federal University of Technology, Akure, Ondo State, Nigeria -
Abstract
Efficacy of using Radial Basis Function Neural Network (RBFNN) and Regression Models (MLR) to estimate trip generation rates in Akure, Nigeria was compared. This sterns from a desire to test more novel modelling techniques besides regression which has hitherto been used in the study area. Data for the study were collected through household questionnaire interview survey in the study area between October 2017 and January 2018. SPSS 22 was used in carrying out data analysis. Correlation analysis showed that Number of household members, (NHM), Number of employed household members, (NEHM), Number of students in household (NSH), Number of Household members with age greater than 12years, (NHM12) and Number of Driver’s license holders in the household, (NDLH) were the household variables having significant influence on home based trips generation rates. The models were compared and validated using their R2 values and Relative Error (RE). Modelling results showed that RBFNN displayed higher accuracy with R2 value of 0.947 and RE of 0.391 as compared to MLR with R2 value of 0.589 and RE of 0.875. The study was able to uphold the capability of artificial neural networks to produce better results in travel demand forecasting areas than regression techniques.
Number of downloads: 626
Keywords:
artificial neural network;
radial basis function;
regression;
model;
trip generation;
travel demand;
References:
Ajayi S. A.; Owolabi A. O.; Busari A. A. 2016. Measures that Enhance Favourable Levels of Service and their Modes of Sustainability on Major Roads in Akure, South-Western Nigeria. In Proceedings of 3rd International Conference on African Development Issues (CU-ICADI 2016), 329-336.
Arliansyah, J.; Hartono, Y. 2015. Trip attraction model using radial basis function neural networks, Procedia Engineering 125: 445-451.
Busari, A. A.; Owolabi, A. O.; Modupe, A. E. 2015a. Modelling the Effect of Income and Car Ownership on Recreational Trip in Akure, Nigeria, International Journal of Scientific Engineering and Technology 4(3): 228-230.
Busari, A. A.; Owolabi, A. O.; Fadugba, O. G.; Olawuyi, O. A. 2015b. Mobility of the Poor in Akure Metropolis: Income and Land Use Approach, Journal of Poverty, Investment and Development 15: 28-33.
Celikoglu, H. B.; Cigizoglu, H. K. 2007. Modelling public transport trips by radial basis function neural networks, Mathematical and computer modelling 45(3-4): 480-489.
Edara, P. K. 2003. Mode choice modelling using artificial neural networks [PhD Thesis]. Virginia Tech, USA.
Engwitch, D. 1992. Towards an Eco-City; Calming the Traffic. Envirobook Publishers, Australia.
Fasakin, J. O.; Basorun, J. O.; Bello, M. O.; Enisan, O. F.; Ojo, B.; Popoola, O. O. 2018. Effect of Land Pricing on Residential Density Pattern in Akure, Nigeria, Advances in Social Sciences Research Journal 5(1): 31-43.
Ferentinou, M. D.; Sakellariou, M. G. 2007. Computational intelligence tools for the prediction of slope performance, Computers and Geotechnics 34(5): 362-384.
Laoye A. A.; Owolabi A. O.; Ajayi S. A. 2016. Indices of Traffic Congestion on Major Roads in Akure, a Developing City in Nigeria, International Journal of Scientific & Engineering Research 7(6): 434-443.
Millennium Cities Initiatives. 2017. Akure, Nigeria. Available from internet: http://mci.ei.columbia.edu/millenium-cities/akure-nigeria/. Accessed November 20, 2017.
Mozolin, M.; Thill, J. C.; Usery, E. L. 2000. Trip distribution forecasting with multilayer perceptron neural networks: A critical evaluation, Transportation Research Part B: Methodological 34(1): 53-73.
Ogunbodede, E. F.; Ale, A. S. 2015. The Use Regression Model in the Forecast of Travel Demand in Akure, Nigeria, Annals of the University of Oradea, Geography Series/Analele Universitatii din Oradea, Seria Geografie 2: 186-194.
Okoko, E.; Fasakin, J. O. 2007. Trip Generation Modelling in Varying Residential Density Zones: An Empirical Analysis for Akure, Nigeria, The Social Sciences 2(1): 13-19.
Owolabi, A.O. 2009. Paratransit Modal Choice in Akure, Nigeria - Applications of Behavioural Models, ITE Journal 79(1): 54-58.
Sarkar, P. K.; Maitri, V.; Joshi, G. J. 2015. Transportation planning: principles practices and policies. First edition. PHI Learning Pvt. Ltd. Delhi.
Yaldi, G.; Taylor, M. A.; Yue, W. L. 2008. Developing a fuzzy-neuro travel demand model (trip distribution and mode choice). In 30th Conference of Australian Institutes of Transport Research, 1-15.
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