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Application of an Artificial Neural Network in Pavement Management System

机译:人工神经网络在路面管理系统中的应用

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摘要

The era of intensive construction of new roads in Croatia is behind us. Today road agencies are focused on maintaining and preserving existing roads. Selection of an appropriate maintenance strategy is a complex task, which includes factors such as the current condition of the pavement, road classification, traffic volume etc. These factors are usually implemented in pavement management systems. The key components of pavement management systems are pavement performance prediction models such as artificial neural networks. This paper analyses the possibility of using artificial neural networks to evaluate existing pavement condition, and its possible application for defining the maintenance strategy of national roads. A backpropagation neural network was applied on 481.3 km of national roads in the Osijek-Baranja County. The obtained results indicated that artificial neural networks could be used for optimization of maintenance or rehabilitation strategies, and for the assessment of pavement condition at the project and network level.
机译:克罗地亚密集建设新道路的时代已经过去。如今,公路部门专注于维护和维护现有道路。选择合适的维护策略是一项复杂的任务,其中包括诸如路面的当前状况,道路分类,交通量等因素。这些因素通常在路面管理系统中实现。路面管理系统的关键组件是路面性能预测模型,例如人工神经网络。本文分析了使用人工神经网络评估现有路面状况的可能性,及其在确定国道养护策略中的可能应用。在Osijek-Baranja县的481.3公里国道上应用了反向传播神经网络。获得的结果表明,人工神经网络可用于优化维护或修复策略,以及在项目和网络级别评估路面状况。

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