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Pavement Performance Prediction through Fuzzy Logic using Marine Corps Air Station Cherry Point, North Carolina Measurements

机译:使用北卡罗来纳州海军陆战队航空站切里波因特的模糊逻辑预测路面性能

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An airfield condition survey and load evaluation was performed at MCAS CHERRY POINT, NORTH CAROLINA by the Pavement Evaluation Team from Atlantic Division, Naval Facilities Engineering Command. The condition survey and load evaluations were performed on all active airfield pavements. The main purpose of this paper is to develop a Fuzzy Logic method for estimating of pavement condition rating by considering severity and extent, pavement distress as input variables and deduct value as output variable. The model was established to predict the performance of flexible and rigid pavements using the parameters routinely collected by Pavement Evaluation Team to characterize the condition of an existing pavement. These parameters were generally obtained by performing falling weight deflectometer tests and monitoring the development of distresses on the pavement surface. The proposed model for predicting pavement performance was characterized by multilayer that led the reasoning process of the IF-THEN fuzzy rules. The proposed fuzzy model showed good generalization capability, and the evaluation of the model performance produced satisfactory results, demonstrating the efficiency and potential of these new mathematical modeling techniques.
机译:海军设施工程司令部大西洋分部的路面评估小组在北卡罗来纳州的MCAS CHERRY POINT进行了机场状况调查和负荷评估。在所有活动机场路面上进行了状况调查和负荷评估。本文的主要目的是通过考虑严重程度和程度,路面险情作为输入变量以及扣除值作为输出变量,开发一种用于评估路面状况等级的模糊逻辑方法。建立该模型以使用路面评估团队常规收集的参数来预测柔性路面和刚性路面的性能,以表征现有路面的状况。这些参数通常是通过进行落锤挠度计测试并监视路面上的应力变化来获得的。提出的路面性能预测模型的特征在于多层模型,该模型主导了IF-THEN模糊规则的推理过程。所提出的模糊模型具有良好的泛化能力,对模型性能的评估产生了令人满意的结果,证明了这些新的数学建模技术的效率和潜力。

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