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Machine learning Strategies for Analyzing Road Traffic Accident 15th

Machine Learning Strategies for Analyzing Road Traffic Accid...

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15th International Conference on Intelligent Human-Computer Interaction (IHCI)

作者： Gupta, Sumit Kumar, Awadhesh BHU Inst Sci Dept Comp Sci Varanasi Uttar Pradesh India BHU Dept Comp Sci MMV Varanasi Uttar Pradesh India

ISBN: (纸本)9783031538261;9783031538278

Road safety and accidents have been an important concern for the entire world and everyone is putting effort into resolving the long-standing problem of road safety and accidents. In every country on earth, there is traffic and reckless driving. This has a negative impact on a lot of pedestrians. They become victims, although having done nothing wrong. The number of traffic accidents is rising quickly due to the enormous increase in road cars. Accidents like these result in harm, impairment, and occasionally even fatalities. Numerous things like weather changes, sharp curves, and human error all contribute to the high number of traffic accidents. In this research paper various machine learning techniques such as, K Nearest Neighbors, Random Forest, Logistic Regression, Decision Tree, and XGBoost etc., are used to investigate why road traffic accidents occur in various nations throughout theworld. For evaluating and analyzing these algorithm several metrics, including precision, recall, accuracy and F1-Score are used to improve the performance of the dataset and predicts accuracy by approximately more than 85%.

关键词： Machine learning algorithm supervised learning feature analysis Road Accident metric parameter

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Road Accident analysis and Prediction of Accident Severity by Using Machine learning in Bangladesh 7

Road Accident Analysis and Prediction of Accident Severity b...

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7th International Conference on Smart Computing & Communications (ICSCC)

作者： Labib, Md Farhan Rifat, Ahmed Sady Hossain, Md Mosabbir Das, Amit Kumar Nawrine, Faria East West Univ Dept Comp Sci & Engn Dhaka Bangladesh

ISBN: (纸本)9781728115573

In recent years, the road accident has become a global problem and marked as the ninth prominent cause of death in the world. Due to the enormous number of road accidents every year, it has become a major problem in Bangladesh. It is entirely inadmissible and saddening to allow its citizen to kill by road accidents. Consequently, to handle this overwhelmed situation, a precise analysis is required. This research paper has been done to analyze traffic accidents more deeply to determine the intensity of accidents by using machine learning approaches in Bangladesh. We also figure out those significant factors that have a clear effect on road accidents and provide some beneficent suggestions regarding this issue. analysis has been done, by using Decision Tree, K-Nearest Neighbors (KNN), Naive Bayes and AdaBoost these four supervised learning techniques, to classify the severity of accidents into Fatal, Grievous, Simple Injury and Motor Collision these four categories. Finally, the best performance is achieved by AdaBoost.

关键词： Accident Severity Machine learning supervised learning feature analysis Road Accident

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