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Uncertainty Management in Rule Based Systems Application to maneuvers Recognition

机译:基于规则的系统应用中的不确定性管理识别

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In this paper we study the uncertainty management in expert systems. This task is very important especially when noised data are used such as in the CASSICE project, which will be presented later. Indeed, the use of a classical expert system in this case will generally produce mediocre results. We investigate the uncertainty management using the Dempster-Shafer theory of evidence and we discuss benefits and disadvantages of this approach by comparing the obtained results with those obtained by an expert system based on the fuzzy logic.
机译:在本文中,我们研究了专家系统的不确定性管理。此任务非常重要,尤其是当使用诸如在磁带项目中的发音数据时,这将在稍后呈现。实际上,在这种情况下使用古典专家系统通常会产生平庸的结果。我们使用Dempster-Shafer证据理论调查不确定性管理,我们通过将获得的结果与由基于模糊逻辑获得的专家系统获得的人进行比较来讨论这种方法的益处和缺点。

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