首页> 外文会议>2011 International symposium on innovations in intelligent systems and applications >Determining amount of bituminous effects on asphalt concrete strength with artificial intelligence and statistical analysis methods
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Determining amount of bituminous effects on asphalt concrete strength with artificial intelligence and statistical analysis methods

机译:用人工智能和统计分析方法确定沥青对沥青混凝土强度的影响

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In this study, an experimental study has been conducted to determine compressive strength of asphalt concrete. The scope of study by preparing 45 Marshall samples Marshall stability experiment was conducted and compressive strength of asphalt concrete was determined. Compressive strength of asphalt concrete as depending on bituminous amount prediction models were developed by using obtained experiment results. Compressive strength of asphalt concrete values as depending on bituminous amount have been estimated on prediction models developed with regression analyses and Artificial Neural Network (ANN) Methods. Results obtained from models were compared with experiment results. Prediction performances of developed models were evaluated as compared. As a result it was determined that possible to estimate the compressive strength of asphalt concrete as depending on bituminous amount with developed ANN model and that ANN model was more successful than regression model for estimating the compressive strength of asphalt concrete.
机译:在这项研究中,进行了一项实验研究,以确定沥青混凝土的抗压强度。制备45个马歇尔样品的研究范围进行了马歇尔稳定性实验,确定了沥青混凝土的抗压强度。利用获得的试验结果,开发了基于沥青量预测模型的沥青混凝土抗压强度。在通过回归分析和人工神经网络(ANN)方法开发的预测模型中,估算了取决于沥青量的沥青混凝土的抗压强度。从模型获得的结果与实验结果进行比较。比较已开发模型的预测性能。结果,确定了使用开发的ANN模型可以根据沥青量估计沥青混凝土的抗压强度,并且ANN模型比回归模型更成功地估计沥青混凝土的抗压强度。

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