Calibrating Trip Distribution Neural Network Models with Different Scenarios of Transfer Functions Used in Hidden and Output Layers
Abstract
Keywords
Full Text:
PDFReferences
S. T. Skias, Methods and procedures for the verification and validation of artificial neural networks. New York, NY: Springer Science+Business Media, 2006.
W. Chen, et al., "Using a Single Dendritic Neuron to Forecast Tourist Arrivals to Japan," IEICE Transactions on Information and Systems, vol. E100.D, pp. 190-202, 2017.
K. Kumar, et al., "Short term traffic flow prediction in heterogeneous condition using artificial neural network," Transport, vol. 30, pp. 397-405, 2015/10/02 2015.
R. Abdul Jabbar and H. Dia, "Predictive Intelligence: A Neural Network Learning System for Traffic Condition Prediction and Monitoring on Freeways," Journal of the Eastern Asia Society for Transportation Studies, vol. 13, pp. 1785-1800, 2019.
W. Guangxing and K. Jiwon, "A Large Scale Neural Network Model for Crash Prediction in Urban Road Networks " in Australasian Transport Research Forum, Auckland, New Zealand, 2017.
W. R. Black, "Spatial interaction modeling using artificial neural networks," Journal of Transport Geography, vol. 3, pp. 159-166, 1995.
M. Dougherty, "A review of neural networks applied to transport," Transportation Research Part C: Emerging Technologies, vol. 3, pp. 247-260, 1995.
H. Wang, et al., "Detecting Transportation Modes Using Deep Neural Network," IEICE Transactions on Information and Systems, vol. E100.D, pp. 1132-1135, 2017.
Y.-J. Byon, et al., "Real-Time Transportation Mode Identiï¬cation Using Artiï¬cial Neural Networks Enhanced with Mode Availability Layers: A Case Study in Dubai," Appled Sciences, vol. 7, 2017.
O. Lozhkina, et al., "Motor transport related harmful PM2.5 and PM10: from onroad measurements to the modelling of air pollution by neural network approach on street and urban level," Journal of Physics: Conference Series, vol. 772, p. 012031, 2016/11 2016.
G. Yaldi, "Improving the Neural Network Testing Performance for Trip Distribution Modelling by Transforming Normalized Data Non-linearly," International Journal on Advanced Science, Engineering and Information Technology, vol. 7, 2017.
G. Yaldi, "Analysing the Behaviour and Performance of Neural Network Trip Distribution Models toward Different Hidden Layer and Node Numbers," presented at the The 11th International Conference of Eastern Asia Society for Transportation Studies, Cebu, Philippines, 2015.
F. Moretti, et al., "Urban traffic flow forecasting through statistical and neural network bagging ensemble hybrid modeling," Neurocomputing, vol. 167, pp. 3-7, 2015/11/01/ 2015.
D. Teodorovic and K. Vukadinovic, Traffic Control and Transport Planning: A Fuzzy Sets and Neural Networks Approach. Massachusetts, USA: Kluwer Academic Publisher, 1998.
M. Mozolin, et al., "Trip distribution forecasting with multilayer perceptron neural networks: A critical evaluation," Transportation Research Part B: Methodological, vol. 34, pp. 53-73, 2000.
A. Dantas, et al., "Neural network for travel demand forecast using GIS and remote sensing," in Neural Networks, 2000. IJCNN 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on, 2000, pp. 435-440 vol.4.
G. Yaldi, et al., "Improving Artificial Neural Network Performance in Calibrating Doubly-Constrained Work Trip Distribution by Using a Simple Data Normalization and Linear Activation Function," in Paper of The 32 Australasian Transportation Research Forum, Auckland, New Zealand. Available at www.patrec.org/atrf.aspx, 2009.
B. M. Wilamowski, et al., "An Algorithm for Fast Convergence in Training Neural Networks," IEEE, vol. 3, pp. 1778-1782, 2001.
G. Zhang, et al., "Forecasting with artificial neural networks:: The state of the art," International Journal of Forecasting, vol. 14, pp. 35-62, 1998.
DOI: http://dx.doi.org/10.18517/ijaseit.10.6.7189
Refbacks
- There are currently no refbacks.
Published by INSIGHT - Indonesian Society for Knowledge and Human Development