在证据组合中补偿不同来源的一种技术

Conference proceedings. IEEE International Conference on Systems, Man, and Cybernetics Pub Date : 1989-11-14 DOI:10.1109/ICSMC.1989.71450

A. Mogre, R. Mclaren, J. Keller

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引用次数: 1

摘要

应用于给定问题的任何决策程序都涉及从不同来源收集相关信息，并在可能的情况下考虑每个来源或一组来源的可靠性。由于知识不足，可能无法隔离不可靠或不良的信息来源。但是，如果一组源向决策算法提供信息，则可以根据其中源的相对一致性来分析这些源作为一个组的影响。一个信息源在同一决策上达成一致的群体比单个信息源支持不同决策的群体更可靠。衡量一个群体不可靠的标准是它的“差异”，这可以弥补群体内部的分歧。给出了支持该群不信度的理论和结果。

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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A technique to compensate for disparate sources in evidence combination

Any decision procedure that is applied to a given problem involves both the gathering of relevant information from different sources and, when possible, accounting for the reliability of each source or group of sources. Due to insufficient knowledge, it may not be possible to isolate an unreliable or poor source of information. However, if a set of sources provides information to a decision algorithm, the effect of these sources as a group could be analyzed in terms of the relative coherence of the sources within it. A group whose sources are in agreement regarding the same decision is more reliable than one in which the individual sources supported different decisions. A measure of the unreliability of a group is its 'disparity', which could compensate for disagreement within a group. Theory and results to support this group unreliability are presented.<>

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Conference proceedings. IEEE International Conference on Systems, Man, and Cybernetics

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