| 基于遗传优化支持向量机的交通事故预测 |
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| 引用本文： | 陈丙锋,朱伟,朱海燕.基于遗传优化支持向量机的交通事故预测[J].交通科技与经济,2013(6):40-42. |
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| 作者姓名： | 陈丙锋 朱伟 朱海燕 |
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| 作者单位： | [1]重庆交通大学交通运输学院,重庆400074 [2]青海民族大学交通与工程系统,青海西宁810007 |
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| 摘 要： | 针对道路交通事故的预测问题，引入基于遗传优化支持向量机算法建立交通事故预测模型。利用遗传算法寻找支持向量机的最优参数组合，并用最优参数构建相应的支持向量机预测模型。仿真计算结果表明，基于遗传算法优化支持向量机模型优于传统的SVM模型，从而可以更有效地对道路交通事故进行预测。
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| 关 键 词： | 道路交通事故 支持向量机 遗传算法 参数优化 预测模型 |
Forecasting model of road traffic accidents based on support vector machine optimized by genetic algorithm |
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| CHEN Bin-feng,ZHU Wei,ZHU Hai-yan.Forecasting model of road traffic accidents based on support vector machine optimized by genetic algorithm[J].Technology & Economy in Areas of Communications,2013(6):40-42. |
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| Authors: | CHEN Bin-feng ZHU Wei ZHU Hai-yan |
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| Institution: | e . School of Traffic Transportation, Chongqing Jiaotong University, Chongqing 400074, China; Dept. of Traffic Transportation, Qinghai Nationality University, Xining 810007, China |
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| Abstract: | According to the forecast problems in traffic accident, it presents a new method by introducing support vector machine and genetic algorithm（GA SVM）. Since the accuracy of forecasting support vector machine depends on a proper setting of its parameters,thus it adopts the genetic algorithm to optimize the training parameters,and obtains an outstanding support vector machine model. The experimental results show that the GA-SVM has greater accuracy than traditional SVM, and is more effective to forecast the traffic accident. |
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| Keywords: | traffic accident support vector machine genelic algorithm parameter optimization forecastingmodel |
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