Author : Noor ul saba
Keyword : Natural language processing, urban traffic management, traffic accident prediction, machine learning, nlp, ml
Subject : Science and technology
Article Type : Original article (research)
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Abstract : Traffic management can be greatly helped by predicting the length of traffic incidents. In this study, we analyze this prediction task as a classification problem on order to generate a more precise real-time prediction of traffic accident duration and utilize the increasing amount of traffic texts in social networks. Traffic accidents cannot be prevented, even with all these resources in the design and construction of automotive safety measures. Both urban and rural regions see a high rate of accidents. By creating precise prediction models that can automatically separate distinct unintentional incidents, patterns related with different situations can be detected. These classifiers will help create safety precautions and Prevent incidents. In this paper use some Machine learning models to analyses the results as much as possible while using limited resources.
Article by : Noor Ul Saba
Article add date : 2022-07-07
How to cite : Noor ul saba. (2022-July-07). Natural language processing and machine learning based prediction for traffic accident. retrieved from https://www.openacessjournal.com/abstract/1091