A Comparative Study of Accident Black Spot Identification: A Crucial Analysis Using Machine Learning and Statistical Approach
Journal Title: International Journal of Experimental Research and Review - Year 2025, Vol 47, Issue 1
Abstract
Identifying black spots in traffic accidents is critical for the urban traffic accident prediction model and better traffic safety management. Several strategies have been used to identify accidents on urban roadways. Some employ Statistical methodologies, while others, more recently, employ Machine Learning approaches. Fuzzy Logic-based algorithms are ideal for predicting car collisions because they can quickly generate complex non-linear relationships between data. A fully fuzzy-based technique, on the other hand, would provide the required user-defined knowledge. Neural Networks are suitable for this purpose because of their sophisticated learning capabilities. As a result, when the driving attributes are employed as a predictor variable in the accident prediction model, a neuro-fuzzy technique will produce the intended outcome.
Authors and Affiliations
Amrita Sarkar, Vandana Bhattacharjee
Keywords
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- EP ID EP765345
- DOI 10.52756/ijerr.2025.v47.007
- Views 16
- Downloads 0
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