| 基于多BP神经网络与D-S融合的车型识别研究 |
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| 引用本文： | 孟亮,戴亚平,戴忠键,刘岩.基于多BP神经网络与D-S融合的车型识别研究[J].北京理工大学学报,2010(S1):144-147. |
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| 作者姓名： | 孟亮 戴亚平 戴忠键 刘岩 |
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| 作者单位： | 北京理工大学 自动化学院,北京 100081;北京理工大学 自动化学院,北京 100081;北京理工大学 自动化学院,北京 100081;北京理工大学 自动化学院,北京 100081 |
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| 基金项目： | 北京市教委共建基金资助项目(200810) |
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| 摘 要： | 为了提高BP神经网络对车型的识别率,克服单个BP神经网络所存在的网络结构和训练样本数量之间的矛盾,针对大量训练样本采取多个BP神经网络进行训练,进而采用训练好的多个网络进行车型识别. 利用D-S理论将各个BP网络的识别结果进行数据融合以改善最终的车型识别结果. 实验结果表明:随着训练样本数量的增加,多BP网络数据融合方法比单BP神经网络有更高的识别率.
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| 关 键 词： | BP神经网络 车型识别 数据融合 D-S理论 |
| 收稿时间： | 2010/3/30 0:00:00 |
Research of Vehicle Type Recognition Based on Multi-BP Networks with D-S Fusion |
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| MENG Liang,DAI Ya-ping,DAI Zhong-jian and LIU Yan.Research of Vehicle Type Recognition Based on Multi-BP Networks with D-S Fusion[J].Journal of Beijing Institute of Technology(Natural Science Edition),2010(S1):144-147. |
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| Authors: | MENG Liang DAI Ya-ping DAI Zhong-jian and LIU Yan |
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| Institution: | School of Automation,Beijing Institute of Technology, Beijing 100081, China;School of Automation,Beijing Institute of Technology, Beijing 100081, China;School of Automation,Beijing Institute of Technology, Beijing 100081, China;School of Automation,Beijing Institute of Technology, Beijing 100081, China |
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| Abstract: | To improve the recognition of vehicle type with BP neural network, overcome the overload of training samples existed in single BP neural network, we try to take more BP neural network corresponding to numerous training samples respectively, and take the networks which are trained to identify the vehicle type. The results of each BP neural network with the D-S method were used to improve the vehicle recognition results. The experimental results show that the method of multi-BP network with D-S fusion has a higher recognition rate than the single BP neural network in the overload of training samples. |
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| Keywords: | BP neural network vehicle type recognition fusion D-S theory |
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