Submodularity issues in value-of-information-based sensor placement

Submodularity issues in value-of-information-based sensor placement
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基于信息值的传感器放置中的子模块化问题

DOI:
10.1016/j.ress.2018.11.010
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发表时间:
2019
影响因子:
8.1
通讯作者:
Pozzi, M.
Pozzi, M.
中科院分区:
工程技术1区
文献类型:
--
作者:
Malings, C.;Pozzi, M.

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信息的价值代表了一种合理的度量,用于指导在不确定情况下支持基础设施系统管理的传感工作的优化。不幸的是,这个度量缺乏子模块化的特性。子模块性可以直观地理解为收益递减属性,因此,当其他可用度量集合较小时,特定度量的增量收益更高。显示此属性的度量可以使用有效的贪婪方法进行优化,并保证结果的接近最优性。在本文中,我们研究了与使用信息度量值优化传感器监测方案相关的子模块化问题。我们说明了贪心优化方法如何使用信息值在某些情况下导致次优解决方案的传感。我们还研究了一种潜在的启发式方法,该方法涉及一个次模替代度量(例如条件熵),可以用来避免这些缺点。
The value of information represents a rational metric for guiding the optimization of sensing efforts to support infrastructure system management under uncertainty. Unfortunately, this metric lacks the property of submodularity. Submodularity can be intuitively understood as a diminishing returns property, whereby the incremental benefit of a specific measurement is higher when the set of other available measures is smaller. Metrics which exhibit this property can be optimized using efficient greedy approaches, with certain guarantees on the near-optimality of the results. In this paper, we examine the issue of submodularity related to the optimization of sensor monitoring schemes using the value of information metric. We illustrate how greedy optimization approaches using value of information can lead to sub-optimal solutions for sensing in certain situations. We also examine how one potential heuristic approach involving a submodular surrogate metric (e.g. the conditional entropy) might be used to avoid some of these shortcomings.
使用贝叶斯网络、决策图和信息价值进行传感器网络优化
DOI: --
发表时间: 2015
期刊:
影响因子: --
作者:
C. Malings;M. Pozzi
通讯作者: M. Pozzi
DOI: 10.1016/j.ress.2016.05.014
发表时间: 2016
期刊: Reliab. Eng. Syst. Saf.
影响因子: --
作者:
Milad Memarzadeh;M. Pozzi
通讯作者: M. Pozzi
DOI: 10.1016/j.ress.2017.11.019
发表时间: 2018-04-01
影响因子: 8.1
作者:
Malings, C.;Pozzi, M.
通讯作者: Pozzi, M.
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DOI: --
发表时间: 2011
期刊:
影响因子: --
作者:
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通讯作者: A. Kiureghian