A model development on GIS-driven data to predict temporal daily collision through integrating Discrete Wavelet Transform (DWT) and Artificial Neural Network (ANN) algorithms; case study: Tehran-Qazvin freeway-Reference-Cited by-同舟云学术

A model development on GIS-driven data to predict temporal daily collision through integrating Discrete Wavelet Transform (DWT) and Artificial Neural Network (ANN) algorithms; case study: Tehran-Qazvin freeway

Published:2021-01-19 Issue: Volume: Page:1-17
ISSN:1010-6049
Container-title:Geocarto International
language:en
Short-container-title:Geocarto International

Author:

Sanayei Reza¹,Vafaeinejad Alireza²,Karami Jalal³,Aghamohammadi Zanjirabad Hossein¹

Affiliation:

1. Department of Remote Sensing and Geographic Information System, Faculty of Natural Resources and Environment, Science and Research Branch, Islamic Azad University, Tehran, Iran

2. Faculty of Civil, Water and Environmental Engineering, Shahid Beheshti University, Tehran, Iran

3. Department of Remote Sensing and Geographic Information System, Faculty of Humanities, Remote Sensing, Tarbiat Modares University, Tehran, Iran

Publisher

Informa UK Limited

Subject

Water Science and Technology,Geography, Planning and Development

Link

https://www.tandfonline.com/doi/pdf/10.1080/10106049.2021.1871669

Reference33 articles.

1. Impact of road traffic injuries on disability rates and long-term care costs in Spain

2. Severity Prediction of Traffic Accident Using an Artificial Neural Network

3. Hyperopt: A Python Library for Optimizing the Hyperparameters of Machine Learning Algorithms

4. A GIS-based comparative study of Dempster-Shafer, logistic regression and artificial neural network models for landslide susceptibility mapping

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