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The normal cloud model of fuzzy inference prediction method for petroleum drilling accident

机译:石油钻井事故模糊推理预测方法的正态云模型

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The cloud model integrates ambiguity, randomness with relationships of the knowledge representation. This paper establishes the normal cloud model to represent membership function. With this method, the problem of unexpected multi-verdict appearing on boundary of membership function is eliminated. By utilizing the fuzzy-c-means clustering algorithm presented in this paper, it is conveniently realized to determine the normal cloud membership function of two important variables in the system of oil drilling accident forecast: the changing of total volume and the flow out rate of drilling slurry. To forecast the well kick accident, the rules of fuzzy inference system expressed with cloud model are extracted. In the example of simulation, the forecast result is a one-dimensional normal random number. This is objectively consilient to uncertainty of accidents in the petroleum drilling.
机译:云模型将模糊性,随机性与知识表示的关系集成在一起。本文建立了表示隶属度函数的普通云模型。通过这种方法,消除了隶属函数边界上出现意外的多重判定的问题。利用本文提出的模糊c均值聚类算法,可以方便地实现确定石油钻井事故预测系统中两个重要变量的正云隶属函数:总体积的变化和流失率。钻井泥浆。为了预测井涌事故,提取了用云模型表达的模糊推理系统的规则。在模拟示例中,预测结果是一维正常随机数。从客观上讲,这与石油钻井事故的不确定性是一致的。

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