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Predicting the Death of Road Accidents in Bangladesh Using Machine Learning Algorithms

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dc.contributor.author Siddik, Md. Abu Bakkar
dc.contributor.author Arman, Md. Shohel
dc.contributor.author Hasan, Afia
dc.contributor.author Jahan, Mahmuda Rawnak
dc.contributor.author Islam, Majharul
dc.contributor.author Biplob, Khalid Been Badruzzaman
dc.date.accessioned 2022-03-01T06:33:16Z
dc.date.available 2022-03-01T06:33:16Z
dc.date.issued 2021
dc.identifier.uri http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/7330
dc.description.abstract Road accidents are now a common occurrence in our country. Every year thousands of people die in these accidents and thousands of people are crippled and cursed. Recently the level of road accidents has increased drastically. In this research paper, the authors discuss previous road accident history profoundly and predict death by applying the machine learning algorithm to get appropriate accuracy in Bangladesh. In this study, we had applied four classification models such as Decision Tree, K-Nearest Neighbors (KNN), Naïve Bayes and Logistic Regression to predict the death of road accidents in Bangladesh. The model was constructed, trained, and tested using the data from “Prothom Alo” newspaper, from which we collected 1237 road crash incidents. This research would be helpful for the policymakers and stakeholders related to the road to take the future steps with the highest accuracy of 88% in the Decision tree algorithm. en_US
dc.language.iso en_US en_US
dc.publisher Scopus en_US
dc.subject Machine learning en_US
dc.subject Supervised learning en_US
dc.subject Classification en_US
dc.subject road accident en_US
dc.title Predicting the Death of Road Accidents in Bangladesh Using Machine Learning Algorithms en_US
dc.type Article en_US


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