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Study on Earthquake Prediction Model Based on Traffic Disaster Data

机译:基于交通灾害数据的地震预报模型研究

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This paper collects data on the damage to the traffic system caused by earthquakes in China in the past two decades, and uses KNN algorithm, SVM algorithm, logistic regression algorithm, naive Bayes algorithm and decision tree algorithm to train the data, then establish earthquake prediction models. The paper introduces the process of preprocessing, modelling, evaluation, and visualization of disaster data. An earthquake disaster inversion model based on traffic data has been established, which can predict the earthquake intensity based on the relevant data provided by the traffic department. The prediction accuracy is relatively accurate, which is very helpful for earthquake prediction and rescue operations.
机译:本文收集了近二十年来中国地震对交通系统造成的破坏数据,并采用KNN算法,SVM算法,logistic回归算法,朴素贝叶斯算法和决策树算法对数据进行训练,进而建立了地震预测模型。楷模。本文介绍了灾难数据的预处理,建模,评估和可视化过程。建立了基于交通数据的地震灾害反演模型,可以根据交通部门提供的相关数据预测地震烈度。预测准确度相对准确,对地震预测和救援工作非常有帮助。

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