Managing the effect of weather on infrastructure projects through advanced analytics

该学生正在解决有关如何将天气预报的不确定性纳入对天气敏感的大型建筑/基础设施项目的项目规划的问题。诸如：>描述项目任务和处理延迟不确定性的交互的适当数学方法是什么？哪种统计推断方法最适用于这个问题？纳入天气延误的概率决策对工程项目工期有何影响？将予以解决。该项目的新颖贡献来自于数学模型的应用，该模型允许将离散和连续数据相结合，作为建筑项目天气延迟的统计推断的一部分。因此，学生正在通过模型开发和应用，以及建筑/基础设施项目对天气的敏感性，发展对统计建模方法的理解。目的：开发一个随机网络模型，为天气敏感型基础设施建设和运营项目活动制定更好的（节省时间和成本）规划和运营决策。目的:1。识别对预先计划的施工和运营活动造成干扰的相关孤立和综合天气事件，这些事件可能最终导致项目延误。这将通过进行详尽的文献审查来实现，同时依靠通过行业合作伙伴提供的过去和当前项目的记录/知识。2. 开发一个建筑项目活动的统计网络模型，使天气影响的不确定性以及预报信息的不确定性能够用于评估与天气有关的项目延误的可能性。评估模型处理天气对建设项目完成的影响的能力。3 .扩展网络模型，以考虑分散项目天气影响的空间变化，并在优化项目天气排序时证明对项目延迟的影响。将整体预测产品纳入模型，以解决不同预测前置时间对项目计划的影响。

The student is addressing questions that inform on how uncertainty in weather forecasting can be incorporated into project planning on large construction/infrastructure projects that are weather-sensitive. Questions such as: > What are the appropriate mathematical approaches to describing project tasks and interactions for handling delay uncertainties? > What methods of statistical inference are best applied to the problem? > How does the inclusion of probabilistic decision-making for weather delays impact on engineering project duration?will be addressed. The novel contribution of the project comes from the application of mathematical models that allow the combination of discrete and continuous data as part of statistical inference of weather delays to construction projects. The student is, therefore, developing understanding of statistical modelling approaches through model development and application, as well as the sensitivity of construction/infrastructure projects to weather.Aim: To develop a stochastic network model for making better (time- and cost-saving) planning and operational decisions for weather-sensitive infrastructure construction and operation project activities. Objectives:1. Identify relate isolated and combined weather events responsible for disruption to pre-planned construction and operation activities that may ultimately result in project delays. This will be performed by conducting an exhaustive literature review while counting on the records/knowledge of past and current projects made available through the industry partner. 2. Develop a statistical network model of construction project activity which enables uncertainty in weather influence, as well as uncertainty in forecast information to be used to evaluate the probability of project delay associated with weather. Evaluate the models ability to address weather impacts on construction project completion.3. Expand the network model to account for spatial variation of weather impacts for dispersed projects and demonstrate impact on project delay when optimising project sequencing for weather.4. Incorporate ensemble forecast products to the models to address the impact of different forecast lead times to project planning.