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From Data to Stochastic Modeling and Decision Making: What Can We Do Better?

机译:从数据到随机建模和决策:我们能做得更好吗?

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摘要

In the past decades we have witnessed a paradigm-shift from scarcity of data to abundance of data. Big data and data analytics have fundamentally reshaped many areas including operations research. In this paper, we discuss how to integrate data with the model-based analysis in a controlled way. Specifically, we consider techniques to quantify input uncertainty and the decision making under input uncertainty. Numerical experiments demonstrate that different ways in decision making may lead to significantly different outcomes in a maintenance problem.
机译:在过去的几十年中,我们目睹了从数据稀缺到大量数据的范式转变。大数据和数据分析从根本上重塑了包括运筹学在内的许多领域。在本文中,我们讨论了如何以可控的方式将数据与基于模型的分析进行集成。具体来说,我们考虑量化输入不确定性的技术以及在输入不确定性下的决策。数值实验表明,决策的不同方式可能导致维护问题的结果大不相同。

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