• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Transportation Research Part B: Methodological >A statistical deterioration forecasting method using hidden Markov model for infrastructure management
【24h】

A statistical deterioration forecasting method using hidden Markov model for infrastructure management

机译：基于隐马尔可夫模型的基础设施管理统计劣化预测方法

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

The application of Markov models as deterioration-forecasting tools has been widely documented in the practice of infrastructure management. The Markov chain models employ monitoring data from visual inspection activities over a period of time in order to predict the deterioration progress of infrastructure systems. Monitoring data play a vital part in the managerial framework of infrastructure management. As a matter of course, the accuracy of deterioration prediction and life cycle cost analysis largely depends on the soundness of monitoring data. However, in reality, monitoring data often contain measurement errors and selection biases, which tend to weaken the correctness of estimation results. In this paper, the authors present a hidden Markov model to tackle selection biases in monitoring data. Selection biases are assumed as random variables. Bayesian estimation and Markov Chain Monte Carlo simulation are employed as techniques in tackling the posterior probability distribution, the random generation of condition states, and the model's parameters. An empirical application to the Japanese national road system is presented to demonstrate the applicability of the model. Estimation results highlight the fact that the properties of the Markov transition matrix have greatly improved in comparison with the properties obtained from applying the conventional multi-stage exponential Markov model.
机译：马尔可夫模型作为恶化预测工具的应用已在基础架构管理的实践中得到了广泛的证明。马尔可夫链模型采用一段时间内视觉检查活动的监控数据，以预测基础设施系统的恶化进度。监视数据在基础架构管理的管理框架中起着至关重要的作用。当然，劣化预测和生命周期成本分析的准确性很大程度上取决于监视数据的可靠性。但是，实际上，监视数据通常包含测量误差和选择偏差，这往往会削弱估计结果的正确性。在本文中，作者提出了一个隐马尔可夫模型来解决监测数据中的选择偏差。选择偏差被假定为随机变量。贝叶斯估计和马尔可夫链蒙特卡罗模拟被用作处理后验概率分布，条件状态的随机生成以及模型参数的技术。提出了在日本国道系统上的经验应用，以证明该模型的适用性。估计结果突出表明，与应用常规多级指数马尔可夫模型获得的性质相比，马尔可夫转移矩阵的性质有了很大的改善。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号