收缩阵列上的可能性证据推理系统

S. Mohiddin, Mohammed Atiquzzaman, T. Dillon
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引用次数: 1

摘要

提出了一种基于可能性证据推理方法的模糊专家系统的收缩阵列实现。一般来说,证据推理系统是计算有限的,而模糊系统比简单的符号推理系统匹配更多的规则。本文提出的可能性证据系统是这两种系统的结合,其计算时间远远大于这两种系统的单独计算时间。为了在这样的系统中加快处理速度,建议的实现是有用的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Possibilistic evidential reasoning systems on systolic arrays
Suggests a systolic array implementation of fuzzy expert systems based on possibilistic evidential reasoning methodology. Evidential reasoning systems are computationally-bounded in general, and fuzzy systems match a larger number of rules than in a simple symbolic reasoning system. The proposed possibilistic evidential system, which is a combination of both types of system, needs much more computation time than either of these two independently. To speed up the processing in such systems, the suggested implementation is useful.<>
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