道路网多特征匹配优化算法
同名道路匹配技术是道路数据集成、更新和融合的重要前提。道路网匹配在智能交通(intelligent transportation system，ITS)与位置服务(location-based service，LBS)等方面具有重要的研究价值和应用意义。本文提出了一种道路网多特征匹配优化算法：首先从形状、距离、语义3方面分别设计了基于面积累积的形状差、综合中值Hausdorff距离和全局加权属性项距离3种相似性度量，以更准确地描述道路待匹配对之间的特征差异；然后通过SVM对相似性特征样本集训练，以构建道路网回归匹配模型；最后利用此模型对未知匹配结果道路待匹配对进行匹配结果预测。大量试验结果表明...
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| Veröffentlicht in: | Ce hui xue bao 2016-05, Vol.45 (5), p.608 |
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| container_title | Ce hui xue bao |
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| creator | 付仲良 杨元维 高贤君 赵星源 范亮 |
| description | 同名道路匹配技术是道路数据集成、更新和融合的重要前提。道路网匹配在智能交通(intelligent transportation system，ITS)与位置服务(location-based service，LBS)等方面具有重要的研究价值和应用意义。本文提出了一种道路网多特征匹配优化算法：首先从形状、距离、语义3方面分别设计了基于面积累积的形状差、综合中值Hausdorff距离和全局加权属性项距离3种相似性度量，以更准确地描述道路待匹配对之间的特征差异；然后通过SVM对相似性特征样本集训练，以构建道路网回归匹配模型；最后利用此模型对未知匹配结果道路待匹配对进行匹配结果预测。大量试验结果表明，本文算法对非线性偏差明显的道路网数据能够实现较高的匹配准确率和召回率，能有效地用于包含多重匹配关系的道路网匹配。 |
| doi_str_mv | 10.11947/j.AGCS.2016.20150388 |
| format | Article |
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| subjects | Algorithms Intelligent transportation systems Location based services Matching Metric space Optimization Optimization algorithms Regression models Roads Semantics Similarity Support vector machines Transportation networks |
| title | 道路网多特征匹配优化算法 |
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