Development of Artificial Neural Network Models to Predict Driver Injury Severity in Traffic Accidents at Signalized Intersections

By H. Abdelwahab, Mohamed A. Abdel-Aty. 2001

325 citations recorded by the source corpus.

Subfields: Building and Construction, Control and Systems Engineering, Safety, Risk, Reliability and Quality

View Paper: https://www.semanticscholar.org/paper/dec93635bd9fc815451d0aae342a546ed4476fe2

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Building and Construction

1. D. Lord
2. Fred L. Mannering
3. Mohammed A. Quddus
4. Peter T. Savolainen
5. Yunlong Zhang
6. Yajie Zou

In Control and Systems Engineering

1. D. Lord
2. Fred L. Mannering
3. Mohammed A. Quddus
4. Peter T. Savolainen
5. Yunlong Zhang

In Safety, Risk, Reliability and Quality

1. Fred L. Mannering
2. D. Lord
3. Mohammed A. Quddus
4. Peter T. Savolainen
5. Chandra R. Bhat
6. Panagiotis Ch. Anastasopoulos
7. Ali Behnood
8. Grigorios Fountas

Citations in the corpus

• The statistical analysis of highway crash-injury severities: a review and assessment of methodological alternatives. (2011, methodology): “For example, a few researchers have used artificial neural networks in the injury severity research literature (Abdelwahab and Abdel-Aty, 2001; Delen et al., 2006; Chimba and Sando, 2009). In broad terms, neural networks search for data patterns and allow for potentially non-linear relationships bet”