基于信念函数的专家知识与数据融合:以废水处理为例

Proceedings of the Fifth International Conference on Information Fusion. FUSION 2002. (IEEE Cat.No.02EX5997) Pub Date : 2002-07-08 DOI:10.1109/ICIF.2002.1021011

S. Populaire, Joëlle Blanc, Thierry Denœux, Philippe Ginestet

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引用次数: 8

摘要

本文提出了一种将专家知识与统计数据信息相结合的方法，用于分类和预测问题。该方法基于(1)基于案例的方法，允许以信念函数的形式从过去的案例中预测感兴趣的数量，(2)建模专家知识的贝叶斯网络，以及(3)通过优化性能标准来优化折扣信息源的调谐机制。该方法应用于预测废水中的化学需氧量溶解度。该方法预计将在小型数据库和部分专家知识可用的情况下有用。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Fusion of expert knowledge with data using belief functions: a case study in waste-water treatment

This paper presents a methodology for combining expert knowledge with information from statistical data, in classification and prediction problems. The method is based on (1) a case-based approach allowing to predict a quantity of interest from past cases in the form of a belief function, (2) Bayesian networks for modelling expert knowledge and (3) a tuning mechanism allowing to optimally discount information sources by optimizing a performance criterion. This methodology is applied to the prediction of chemical oxygen demand solubility in waste-water The approach is expected to be useful in situations where both small databases and partial expert knowledge are available.

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Proceedings of the Fifth International Conference on Information Fusion. FUSION 2002. (IEEE Cat.No.02EX5997)

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