A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Modeling Traffic Crashes on Rural and Suburban Highways Using Ensemble Machine Learning Methods
https://orcid.org/http://orcid.org/0000-0002-2419-1118
https://orcid.org/http://orcid.org/0000-0002-4463-2785
In this research work, clustering techniques were used to characterize crashes occurring on rural and suburban highways in Jordan, while support vector machines were used to compare the classification performance of the resulting clusters with that obtained without clustering, the data used included 10219 crashes obtained from the Jordanian Traffic Institute for (2014–2018). Support vector machines with four kernel functions were used to measure the classification performance using different clustered and non-clustered data. RBF kernel showed a prominent performance in classifying injury severity levels as indicated by the results obtained by the performance measures used (accuracy, precision, recall, and F1-score). It was found that classification performance as measured by support vector machines of the clustered sets was superior to that obtained using the non-clustered set. All clustered models were remarkably able to predict injury severity levels using the RBF kernel with F1-score ranging from 72% to 81%.
Modeling Traffic Crashes on Rural and Suburban Highways Using Ensemble Machine Learning Methods
https://orcid.org/http://orcid.org/0000-0002-2419-1118
https://orcid.org/http://orcid.org/0000-0002-4463-2785
In this research work, clustering techniques were used to characterize crashes occurring on rural and suburban highways in Jordan, while support vector machines were used to compare the classification performance of the resulting clusters with that obtained without clustering, the data used included 10219 crashes obtained from the Jordanian Traffic Institute for (2014–2018). Support vector machines with four kernel functions were used to measure the classification performance using different clustered and non-clustered data. RBF kernel showed a prominent performance in classifying injury severity levels as indicated by the results obtained by the performance measures used (accuracy, precision, recall, and F1-score). It was found that classification performance as measured by support vector machines of the clustered sets was superior to that obtained using the non-clustered set. All clustered models were remarkably able to predict injury severity levels using the RBF kernel with F1-score ranging from 72% to 81%.
Modeling Traffic Crashes on Rural and Suburban Highways Using Ensemble Machine Learning Methods
https://orcid.org/http://orcid.org/0000-0002-2419-1118
https://orcid.org/http://orcid.org/0000-0002-4463-2785
In this research work, clustering techniques were used to characterize crashes occurring on rural and suburban highways in Jordan, while support vector machines were used to compare the classification performance of the resulting clusters with that obtained without clustering, the data used included 10219 crashes obtained from the Jordanian Traffic Institute for (2014–2018). Support vector machines with four kernel functions were used to measure the classification performance using different clustered and non-clustered data. RBF kernel showed a prominent performance in classifying injury severity levels as indicated by the results obtained by the performance measures used (accuracy, precision, recall, and F1-score). It was found that classification performance as measured by support vector machines of the clustered sets was superior to that obtained using the non-clustered set. All clustered models were remarkably able to predict injury severity levels using the RBF kernel with F1-score ranging from 72% to 81%.
Modeling Traffic Crashes on Rural and Suburban Highways Using Ensemble Machine Learning Methods
KSCE J Civ Eng
Mujalli, Randa Oqab (author) / Al-Masaeid, Hashem (author) / Alamoush, Shrooq (author)
KSCE Journal of Civil Engineering ; 27 ; 814-825
2023-02-01
12 pages
Article (Journal)
Electronic Resource
English
Stochastic modelling for traffic crashes on non urban highways in India
| British Library Conference Proceedings | 2006
Fatality Risk of Intersection Crashes on Rural Undivided Highways in Alberta, Canada
| British Library Online Contents | 2010
Clear Zone Requirements for Suburban Highways
| British Library Online Contents | 1995
Highways Agency - Clearing up after crashes
Online Contents | 2008
Accidents on Suburban Highways -- Tennessee's Experience
| Online Contents | 1995