Detecting crash hotspots using grid and density-based spatial clustering-Reference-Cited by-同舟云学术

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Detecting crash hotspots using grid and density-based spatial clustering

Published:2021-02-02 Issue: Volume: Page:1-13
ISSN:0965-092X
Container-title:Proceedings of the Institution of Civil Engineers - Transport
language:en
Short-container-title:Proceedings of the Institution of Civil Engineers - Transport

Author:

Ganjali Khosrowshahi Amin¹,Aghayan Iman²^ORCID,Kunt Mehmet Metin³^ORCID,Choupani Abdoul-Ahad⁴

Affiliation:

1. Research Assistant, Faculty of Civil Engineering, Shahrood University of Technology, Shahrood, Iran

2. Assistant Professor, Faculty of Civil Engineering, Shahrood University of Technology, Shahrood, Iran (corresponding author: )

3. Associate Professor, Department of Civil Engineering, Eastern Mediterranean University, Gazimagusa KKTC, Mersin 10, Turkey

4. Assistant Professor, Faculty of Civil Engineering, Shahrood University of Technology, Shahrood, Iran

Publisher

Thomas Telford Ltd.

Subject

Transportation,Civil and Structural Engineering

Link

https://www.icevirtuallibrary.com/doi/pdf/10.1680/jtran.20.00028

Reference48 articles.

1. Extended Traffic Crash Modelling through Precision and Response Time Using Fuzzy Clustering Algorithms Compared with Multi-layer Perceptron

2. Automatic subspace clustering of high dimensional data for data mining applications

3. Analysis of Traffic Accident in Riyadh Using Clustering Algorithms

4. Density-based clustering for road accident data analysis

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1. Editorial;Proceedings of the Institution of Civil Engineers - Transport;2023-07

2. Genetic-Based Keyword Matching DBSCAN in IoT for Discovering Adjacent Clusters;Computer Modeling in Engineering & Sciences;2023

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