Using hybrid Data Mining algorithm for Analysing road accidents Data Set

机译：使用混合数据挖掘算法分析道路事故数据集

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Nowadays, road safety has become an important issue in the urban areas due to the high vehicle density. Road safety can be improved by reducing the accidents. Road accident causes traffic hindrance which has become intolerable especially in big-cities. Therefore, analyzing the road accidents accurately can help to solve the problem of traffic crashes. In our project, we propose a hybrid model that combines both K-Nearest Neighbor and Support Vector Machines algorithm for road accident analysis and prediction of accident type, which is based on the hierarchical-learning approach. The accident types are classified as crash, drunk & drive, fire and skid. Our proposed model uses the combination of both KNN and SVM algorithms with the historical datasets collected from UCI Repository. This analyzed data will be more useful to suggest better safety measures to avoid traffic crashes. We experimentally analyze the performance of both KNN and SVM algorithms using R programming with large accident datasets. Results show that our hybrid model enhances the accuracy of road accident analysis.

机译：如今，由于车辆密度高，道路安全已成为城市中的重要问题。减少事故可以改善道路安全。道路交通事故会造成交通障碍，在大城市中尤其如此。因此，准确分析道路交通事故可以帮助解决交通事故的问题。在我们的项目中，我们提出了一种基于层次学习方法的混合模型，该模型结合了K最近邻算法和支持向量机算法，用于道路事故分析和事故类型预测。事故类型分为撞车，酒后驾车，火灾和打滑。我们提出的模型结合了KNN和SVM算法以及从UCI存储库中收集的历史数据集。经过分析的数据将对建议更好的安全措施以避免交通事故更为有用。我们使用大型事故数据集的R编程实验性地分析了KNN和SVM算法的性能。结果表明，我们的混合模型提高了道路事故分析的准确性。

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《International Conference on Computing and Communications Technologies》|2019年|7-13|共7页
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G. Parathasarathy; T.R Soumya; Y. Justin Das; J. Saravanakumar; A. Anigo Merjora;
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Support vector machines; Classification algorithms; Road accidents; Prediction algorithms; Clustering algorithms; Data mining;

机译：支持向量机;分类算法;道路事故;预测算法;聚类算法;数据挖掘;

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1. A DATA MINING FRAMEWORK TO ANALYZE ROAD ACCIDENT DATA USING MAP REDUCE METHODS CCMF AND TCAMP ALGORITHMS [J] . S. Nagendra Babu, J. Jebamalar Tamilselvi International journal of simulation: systems, science and technology . 2018,第5aaPagea1期

机译：使用地图分析道路事故数据的数据挖掘框架减少方法CCMF和TCAMP算法
2. A DATA MINING FRAMEWORK TO ANALYZE ROAD ACCIDENT DATA USING MAP REDUCE CCMF AND TCAMP ALGORITHMS [J] . S. Nagendra Babu, J. Jebamalar Tamilselvi International journal of simulation: systems, science and technology . 2018,第6aaPagea3期

机译：使用地图分析道路事故数据的数据挖掘框架减少CCMF和TCAMP算法
3. Analysing factors related to slipping, stumbling, and falling accidents at work: Application of data mining methods to Finnish occupational accidents and diseases statistics database [J] . Noora Nenonen Applied Ergonomics . 2013,第2期

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4. Using hybrid Data Mining algorithm for Analysing road accidents Data Set [C] . G. Parathasarathy, T.R Soumya, Y. Justin Das, International Conference on Computing and Communications Technologies . 2019

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机译：在道路资产管理数据上使用数据挖掘来分析交通事故

Using hybrid Data Mining algorithm for Analysing road accidents Data Set

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