| 基于改进BP神经网络的路面状态识别研究 |
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| 引用本文： | 李虹,冯彦辉,林君. 基于改进BP神经网络的路面状态识别研究[J]. 微计算机信息, 2010, 0(2) |
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| 作者姓名： | 李虹 冯彦辉 林君 |
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| 作者单位： | 吉林大学;吉林省水利科学研究院;吉林省吉辉科技股份有限公司; |
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| 基金项目： | 科技部科研院所技术开发研究专项资金《气象通量采集系统和路面状态传感器》(NO:2007505) |
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| 摘 要： | 解决路面气象状态的识别问题并满足一定的精度要求,是高速公路气象监测研究中的一个关键问题。本文提取、和三种彩色模型信息组成特征向量;提出一种附加动量法和自适应学习率相结合的改进BP算法;在此基础上建立了非线性识别模型,并将该模型应用于路面状态识别试验。实验结果表明该模型能准确有效地识别路面气象状态。
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| 关 键 词： | 神经网络 颜色模型 改进BP算法 非线性系统 路面状态 |
Study on Road Surface Condition Recognition based on BP Network Improved |
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| LI Hong FENG Yan-hui LIN Jun. Study on Road Surface Condition Recognition based on BP Network Improved[J]. Control & Automation, 2010, 0(2) |
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| Authors: | LI Hong FENG Yan-hui LIN Jun |
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| Abstract: | To resolve recognition problem of road surface conditions and satisfy measure accuracy is one key of freeway meteorology monitoring study. Three kinds of,and color models extracted constitute feature vectors. A BP neural network algorithm improved by momentum and self-adaptive learning rate is presented. On the basis of these, a model of the nonlinear system is set up and applied in road surface conditions identification. Experimental results show that the model can identify road surface meteorology more ac... |
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| Keywords: | neural network BP algorithm improved nonlinear system road surface meteorology |
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