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Bayesian Approach to Intelligent Control and Its Relation to Fuzzy Control

机译:贝叶斯智能控制方法及其与模糊控制的关系

摘要

In many application areas including economics, experts describe their knowledge by using imprecise (u22fuzzyu22) words from natural language. To design an automatic control system, it is therefore necessary to translate this knowledge into precise computer-understandable terms. To perform such a translation, a special semi-heuristic fuzzy methodology was designed. This methodology has been successfully applied to many practical problem, but its semi-heuristic character is a big obstacle to its use: without a theoretical justification, we are never 100% sure that this methodology will be successful in other applications as well. It is therefore desirable to come up with either a theoretical justification of exactly this methodology, or with a theoretically justified modification of this methodology. In this paper, we apply the Bayesian techniques to the above translation problem, and we analyze when the resulting methodology is identical to fuzzy techniques -- and when it is different.
机译:在包括经济学在内的许多应用领域中,专家都使用自然语言中不精确的词来描述他们的知识。因此,在设计自动控制系统时,有必要将这些知识转换为计算机可以理解的精确术语。为了进行这种翻译,设计了一种特殊的半启发式模糊方法。该方法论已成功地应用于许多实际问题,但其半启发式特性是其使用的一大障碍:没有理论上的证明,我们永远不会百分百确定该方法论在其他应用程序中是否也会成功。因此,需要提出一种确切地对该方法论进行理论证明或对该方法学进行理论上的修改。在本文中,我们将贝叶斯技术应用于上述翻译问题,并分析了所得方法何时与模糊技术相同-以及何时不同。

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