| 基于BP神经网络沥青混合料低温弯拉应变预测模型 |
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| 引用本文： | 谭忆秋,公维强,徐慧宁.基于BP神经网络沥青混合料低温弯拉应变预测模型[J].沈阳建筑工程学院学报(自然科学版),2009,25(2):224-229. |
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| 作者姓名： | 谭忆秋 公维强 徐慧宁 |
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| 作者单位： | 谭忆秋,徐慧宁,TAN Yiqiu,XU Huining(哈尔滨工业大学交通科学与工程学院,黑龙江哈尔滨,150090);公维强,GONG Weiqiang(中交公路规划设计院有限公司,北京,100010)
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| 基金项目： | 国家科技支撑计划重点项目，教育部高等学校博士学科点专项科研基金 |
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| 摘 要： | 目的分析影响沥青混合料低温弯拉应变的因素,预测沥青混合料低温弯拉应变.方法基于Mablab7.1平台,应用灰色关联熵法分析了影响沥青混合料低温弯拉应变的因素,建立了结构为9-14-1的三层沥青混合料低温弯拉应变的BP神经网络预测模型.结果根据灰色关联熵法分析,确定了5℃延度、针入度指数PI、当量脆点t1.2、当量软化点t800、FAc比、25℃针入度、FAf比、软化点、CA比等9个影响因素作为神经网络模型的输入因素.通过43组试验数据对BP神经网络模型进行了学习训练,并用另外5组试验数据对模型进行了检验.预测结果与实测结果误差在工程要求精度范围以内.结论预测结果与实测结果的拟和程度较高,预测模型可信,可用于沥青混合料低温性能预测.
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| 关 键 词： | 沥青混合料 低温弯拉应变 BP神经网络 预测模型 灰色关联熵 |
Research on the Application of Neural Network in the Model for Limiting Flexural Strain of Asphalt Mixture at Low Temperature |
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| TAN Yiqiu,GONG Weiqiang,XU Huining.Research on the Application of Neural Network in the Model for Limiting Flexural Strain of Asphalt Mixture at Low Temperature[J].Journal of Shenyang Archit Civil Eng Univ: Nat Sci,2009,25(2):224-229. |
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| Authors: | TAN Yiqiu GONG Weiqiang XU Huining |
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| Affiliation: | TAN Yiqiu, GONG Weiqiang,XU Huining ( 1. School of Traffic Science and Engineering, Harbin Institute of Technology, Harbin China, 150090; 2. China Highway Planning and Design Institute Consultants ,Inc. ,Beijing ,China 100010) |
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| Abstract: | Limiting flexural strain at low temperature is the key parameter to reflect the low temperature crack resistance of asphalt mixtures. Precisely predicting the limiting flexural strain at low temperature is of great importance in the design of asphalt mixtures and production. With the aid of grey entropy grade analysis, the parameters that affect the limiting flexural strain at low temperature were analyzed. Prediction model of the limiting flexural strain at low temperature was set by BP neural network. The model was trained by 43 test data, and was proved by other 5 test data. Practical application demonstrated that the prediction model met the practical use. |
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| Keywords: | asphalt mixture flexural strain at low temperature BP neural network prediction model grey entropy relation grade |
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