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贝叶斯网络在法庭土壤分析中的应用。

Use of Bayesian networks in forensic soil casework.

机构信息

Netherlands Forensic Institute, P.O. Box 24044, 2490 AA The Hague, The Netherlands; Utrecht University, Department of Physical Geography, P.O. Box 80115, 3508 TC Utrecht, The Netherlands.

Utrecht University, Department of Physical Geography, P.O. Box 80115, 3508 TC Utrecht, The Netherlands.

出版信息

Sci Justice. 2022 Mar;62(2):229-238. doi: 10.1016/j.scijus.2022.02.005. Epub 2022 Feb 16.

Abstract

Forensic soil comparisons can be of high evidential value in a forensic case, but become complex when multiple methods and factors are considered. Bayesian networks are well suited to support forensic practitioners in complex casework. This study discusses the structure of a Bayesian network, elaborates on the in- and output data and evaluates two examples, one using source level propositions and one using activity level propositions. These examples can be applied as a template to construct a case specific network and can be used to assess sensitivity of the target output to different factors and identify avenues for research.

摘要

法庭土壤比较在法庭案件中具有很高的证据价值,但当考虑多种方法和因素时,会变得复杂。贝叶斯网络非常适合支持法庭从业人员处理复杂案件。本研究讨论了贝叶斯网络的结构,详细说明了输入和输出数据,并评估了两个示例,一个使用源级命题,一个使用活动级命题。这些示例可作为构建特定于案件的网络的模板,并可用于评估目标输出对不同因素的敏感性,并确定研究方向。

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