TY - JOUR
AU1 - Ghasempoor, Zeynab
AU2 - Behzadi, Saeed
AU3 - 
AB - International Journal of Geography and Geology 2022 Vol. 11, No. 2, pp. 62-71. ISSN(e): 2305-7041 ISSN(p): 2306-9872 DOI: 10.18488/10.v11i2.3166 © 2022 Conscientia Beam. All Rights Reserved. PREDICTING TRAFFIC DATA IN GIS USING DIFFERENT NEURAL NETWORK METHODS Faculty of Civil Engineering, Shahid Rajaee Teacher Training University, Zeynab Tehran, Iran. 1+ Ghasempoor Email: zeynabghasempoor8@gmail.com Saeed Behzadi Department of Surveying Engineering, Faculty of Civil Engineering, Shahid Rajaee Teacher Training University, Tehran, Iran. (+ Corresponding author) Email: behzadi.saeed@gmail.com ABSTRACT Article History Traffic is one of the most influential factors in choosing the route to reach the Received: 8 August 2022 destination. It can be said that a large percentage of people prefer a long but low traffic Revised: 22 September 2022 route than a short route with heavy traffic. Therefore, traffic is a very determining Accepted: 5 October 2022 Published: 13 October 2022 factor in societies, especially in metropolitan areas. The issue of traffic forecasting is another important factor in the field of traffic. In such a way that the traffic of the Keywords coming days can be predicted based on the traffic of the previous days. In this paper, Bayesian traffic forecasting in the coming days is done using a neural network 
TI - Predicting Traffic Data in GIS using Different Neural Network Methods
JF - International Journal of Geography and Geology
DO - 10.18488/10.v11i2.3166
DA - 2022-10-13
UR - https://www.deepdyve.com/lp/unpaywall/predicting-traffic-data-in-gis-using-different-neural-network-methods-0f0DuEzfB8
DP - DeepDyve
ER -