| 基于PSO—SVM的交通事故预测 |
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| 引用本文： | 赵安岭,张建旭,张子阳.基于PSO—SVM的交通事故预测[J].交通科技与经济,2013(6):48-50. |
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| 作者姓名： | 赵安岭 张建旭 张子阳 |
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| 作者单位： | 重庆交通大学交通运输学院,重庆400074 |
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| 摘 要： | 为更加准确地描述道路交通事故发生的规律，结合粒子群算法和支持向量机理论，提出一种粒子群算法（Ps0）优化支持向量机（SVM）的道路交通事故预测模型，并用相应的数据进行仿真研究。结果表明，基于粒子群算法优化支持向量机模型（PS（）ISVM）NNNNNNN，能较好地契合道路交通事故的变化趋势。
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| 关 键 词： | 道路交通事故 支持向量机 粒子群算法 预测模型 |
Forecasting traffic accidents based on PSO-SVM |
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| ZHAO An-ling,ZHANG Jian-xu,ZHANG Zi-yang.Forecasting traffic accidents based on PSO-SVM[J].Technology & Economy in Areas of Communications,2013(6):48-50. |
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| Authors: | ZHAO An-ling ZHANG Jian-xu ZHANG Zi-yang |
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| Institution: | (School of Traffic Transportation,Chongqing Jiaotong University, Chongqing 400074,China) |
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| Abstract: | In order to describe the rule of traffic accident more accurately, it introduces a new method of linking up support vector machine and particle swarm algorithm（PSO-SVM）. And a satisfactory result is accomplished. The experimental results indicate that the PSO-SVM has greater accuracy than traditional SVM, and complies with the traffic accident trend. |
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| Keywords: | traffic accident support vector machine particle swarm algorithm forecasting model |
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