基于多值逻辑的知识提取与实时更新方法

E. Gegov, B. Vatchova, E. Gegov
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引用次数: 3

摘要

常见的知识派生方法是基于统计过程的,没有实时更新知识的算法。在这项工作中,算法使用逻辑和统计程序成功实现,其中输入灵活的实验数据阵列,以便删除旧数据并添加新数据。将这些数据分组打包,转化为多值逻辑函数的逻辑值。该函数伴随着其值出现的概率,该概率是实时计算的。这样,就形成了一种新的结构,称为多值逻辑概率函数(MLPF),它同时表达了逻辑和概率两种相互关联的对应关系。通信是实时更新的。MLPF是一个实时更新的生产规则系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multi-valued logical method for knowledge extraction and updating in real time
Familiar methods for knowledge derivation are based on statistical procedures, which are not accompanied by algorithms for updating of knowledge in real time. In this work, the algorithms are implemented successfully using both logical and statistical procedures whereby flexible arrays of experimental data is entered such that older data is removed and newer data is added. These data are packed together in groups and transformed into logical values of functions of multi-valued logic. The functions are accompanied by probability of occurrence of its values, which is evaluated in real time. In this way, a new construction is formed called multi-valued logical probability function (MLPF), which expresses simultaneously two mutually related correspondences-logical and probabilistic. The correspondences are updated in real time. MLPF is a system of production rules, which are updated in real time.
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