Risk Identification & Quantification in Complex Human-Natural Systems via Convergent Data Intensive Research
Risk Identification & Quantification in Complex Human-Natural Systems via Convergent Data Intensive Research
复制标题
风险识别
DOI：
10.1145/3447548.3469480
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发表时间：
2021
期刊：
影响因子：
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通讯作者：
Matteson, David S.
中科院分区：
文献类型：
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作者：
Schafer, Toryn L.J.;McGranaghan, Ryan M.;Getmansky Sherman, Mila;Feng, Mei-Ling E.;Owolabi, Olukunle O.;Ryan, Sean E.;Düker, Marie-Christine;Jauch, Michael;Matteson, David S.
人类-自然系统涉及复杂的相互依赖的过程，但特定领域的过程传统上是在非重叠的研究孤岛中研究的。用于多层动态互连分析的预测风险调查系统（PRISM）是一组跨多个域的协作者，他们致力于发现特定于域风险之间的数据驱动连接。我们将跨学科的风险评估方法带到我们的KDD'21研讨会。我们的研讨会是迈向系统性风险分析的整体方法的一步，欢迎在风险和复杂系统的前沿应用和技术研究的演讲者。
Human-natural systems involve complex interdependent processes, but domain specific processes are traditionally studied in non-overlapping research silos. The Predictive Risk Investigation SysteM (PRISM) for multi-layer dynamic interconnection analysis is a group of collaborators across multiple domains who work to discover data driven connections specifically among domain risks. We bring our inter-disciplinary approach to risk assessment to our KDD'21 workshop. Our workshop is a step toward a holistic approach to systemic risk analysis by welcoming speakers in applied and technical research at the forefront of risk and complex systems.