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Pavement rehabilitation and maintenance prioritization of urban roads using fuzzy logic

机译:基于模糊逻辑的城市道路路面修复与养护优先

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With regard to limits in budget, inevitably, one must choose prioritized projects in pavements rehabilitation and maintenance process. This paper looks into prioritization based upon a model including all effects of important factors like pavement condition index, traffic volume, road width as well as rehabilitation and maintenance cost. Since defining a model that introduces all those factors was difficult, a more advanced modeling named fuzzy logic was referred for the problem of prioritization. Although analytical hierarchy process can be used for decision making process as well, fuzzy modeling lets one have more precise choices for the outcome. Finally with the help of MATLAB software and coded M-files, inference engines such as Product engine, Dienes-Rescher and Lukasiewicz were all tested and the logical favorite separation for this application was found in product inference engine. As a case study some streets located in district No. 6 of Tehran municipality were selected and the favorite mathematical model was executed on those streets. This model was used for prioritizing these 131 sections.
机译:关于预算限制,不可避免地,必须在路面修复和维护过程中选择优先项目。本文基于模型对优先级进行了研究,该模型包括重要条件的所有影响,例如路面状况指数,交通量,道路宽度以及修复和维护成本。由于定义引入所有这些因素的模型很困难,因此针对优先级问题引用了一个更高级的模型,称为模糊逻辑。尽管分析层次结构过程也可以用于决策过程,但是模糊建模使人们可以对结果进行更精确的选择。最后,借助MATLAB软件和编码的M文件,对推论引擎(例如Product引擎,Dienes-Rescher和Lukasiewicz)都进行了测试,并且在产品推论引擎中找到了该应用程序的逻辑上最喜欢的分离方式。作为案例研究,选择了位于德黑兰市第6区的一些街道,并在这些街道上执行了喜欢的数学模型。该模型用于确定这131个部分的优先级。

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