Application of Machine-Learning in Network-Level Road Maintenance Policy-Making: The Case of Iran

作者：

Highlights：

• Machine-learning algorithms were adopted to predict the cost of maintenance policies.

• The Markov Chain model was used to predict the post-maintenance network condition.

• Optimal policies were found based on the optimization of cost and network condition.

• The paper contributes to the sustainable development goals #9, #11, and #13.

摘要

•Machine-learning algorithms were adopted to predict the cost of maintenance policies.•The Markov Chain model was used to predict the post-maintenance network condition.•Optimal policies were found based on the optimization of cost and network condition.•The paper contributes to the sustainable development goals #9, #11, and #13.

论文关键词：Road maintenance policy-making,Maintenance cost optimization,Network PCI,Gradient boosting regression,Markov Chain model,TOPSIS

论文评审过程：Received 29 September 2020, Revised 27 October 2021, Accepted 21 November 2021, Available online 29 November 2021, Version of Record 4 December 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.116283