An artificial neural network-based model for predicting paratransit travel time-Reference-Cited by-同舟云学术

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An artificial neural network-based model for predicting paratransit travel time

Published:2024-08-03 Issue:1 Volume:11 Page:
ISSN:2331-1916
Container-title:Cogent Engineering
language:en
Short-container-title:Cogent Engineering

Author:

Ukam George¹²^ORCID,Adams Charles¹^ORCID,Adebanji Atinuke³^ORCID,Ackaah Williams⁴

Affiliation:

1. Regional Transport Research and Education Centre, Kumasi (TRECK), Department of Civil Engineering, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana

2. Department of Civil Engineering, University of Cross River State (UNICROSS), Calabar, Nigeria

3. Department of Statistics and Actuarial Sciences, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana

4. Council for Scientific and Industrial Research (CSIR) - Building and Road Research Institute, Kumasi, Ghana

Funder

Regional Transport Research and Education Centre, Kumasi (TRECK) of the Department of Civil Engineering, Kwame Nkrumah University of Science and Technology, Kumasi (KNUST), Ghana.

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/23311916.2024.2386383

Reference65 articles.

1. Ajayi, S. A., Quadri, H. A., & Sani, R. O. (2018). predictive modeling of travel time on major roads in Akure, Nigeria.’ Proceedings of NBRRI International Conf. on Sustainable Development Goals and Nigerian Construction Industry, pp. 1–12.

2. Prediction of Bus Travel Time Using ANN: A Case Study in Delhi

3. PREDICTION OF BUS TRAVEL TIME USING ARTIFICIAL NEURAL NETWORK

4. Dynamic Bus Travel Time Prediction Models on Road with Multiple Bus Routes

5. Travel-Time Prediction Methods: A Review

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