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不确定知识的英文

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"不确定知识"怎么读用"不确定知识"造句

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  • uncertain knowledge

例句与用法

  • Rough sets theory , an intelligent method for mining and processing imprecise and uncertain knowledge , has got great improvement
    粗糙集( roughsets )理论是一门日益成熟起来的用于不精确,不确定知识挖掘与处理的重要智能技术方法。
  • The bayesian network ( bn ) proposed by pearl is a new mechanism for uncertain knowledge representation based on probability theory and graph theory
    贝叶斯网络( bayesiannetwork , bn )是pearl提出的一种基于概率论和图论的不确定知识表示模型。
  • Rough set theory is a new mathematical tool that deals with vagueness and uncertainty . at present , the data mining method based on rough set theory has become one of the main methods of data mining
    粗糙集理论是一种处理模糊和不确定知识的数学工具:目前,基于粗糙集理论的数据挖掘方法已经成为主要的数据挖掘方法之一。
  • Rough sets theory , proposed by professor z . pawlak in 1980s , is a theoretical method that researches not only vagueness and uncertainty of knowledge , but also expression and induction of data
    粗糙集理论是波兰华沙理工大学pawlak教授在20世纪80年代初提出的一种研究不完整、不确定知识和数据的表达、学习、归纳的理论方法。
  • Bayesian network ( bn ) is one of the most effective theoretical models for uncertainty knowledge expression and reasoning . it can be applied to decision with various dependent factors
    贝叶斯网络是目前不确定知识表达和推理领域最有效的理论模型之一,适用于不确定性和概率性的知识表达和推理,特别适用于有条件地依赖多种控制因素的决策。
  • Recently , rough sets theory has been one of the important techniques ; the polish scientist z . pawlak brought forward this theory firstly in 20 century 80 years . it is a kind of tool for dealing with imprecise and uncertain problem
    近年来,基于粗糙集理论的知识获取方法已成为一种重要的方法,它是二十世纪八十年代由波兰科学家z . pawlak提出的一种新的处理不精确、不确定知识的软计算工具。
  • Rough set theory is a data mining approach capable of dealing with incomplete and inaccurate data , and it has been successfully applied to artificial intelligence and knowledge discovery , pattern recognition and classification , and fault detection
    粗糙集理论是数据挖掘的方法之一,它是处理模糊和不确定知识的一种数学工具,已在人工智能与知识发现,模式识别与分类,故障检测等方面得到了较好应用。
  • Rough set theory is a powerful tool in deal with vagueness and irrelevant information . it can be used to reduce features and extract rules . in this paper , rough set theory is firstly applied to extract features of the power plant condenser
    粗糙集是一种处理模糊和不确定知识的数学工具,它的最大优点是无需提供除问题相关的数据集合以外的任何先验信息,比较适合发现数据中隐含的、潜在有用的知识。
  • Rough set theory is a powerful tool in dealing with vague and uncertain information . in this paper , by analyzing the fault characteristics of liquid rocket engine and the rough set method , rough set theory was applied to mine the hot - firing test data of liquid rocket engine
    粗糙集是一种处理模糊和不确定知识的数学工具,在分析液体火箭发动机故障和粗糙集理论特点的基础上,将粗糙集理论应用于液体火箭发动机试车数据挖掘中。
  • Bn is network structure with clarity semantics . lt exploits the structure of the domain to allow a compact representation of complex joint probability distribution . its sound probabilistic semantics , explicit encoding of relevance relationships , inference algorithms and learning algorithms that are fairly efficient and effective in pratice , and decision - making mechanism of facility , have led bn to enter the artificial intelligence ( ai ) mainstream . for the reasons that they have produced more and more practical values and economic profits in many important application fields , such as modern expert systems , diagnosis engines , decision support systems , and data mining systems , researchers from both industry and academia are thus taking them much seriously
    它具有清晰语义的网络结构;它揭示领域对象的内在结构,是复杂全概率分布的紧凑表示方式;其坚实的理论基础、知识结构的自然表述方式、灵活的推理能力、方便的决策机制及有效的学习能力使其成为一种主要的不确定知识的处理方法。贝叶斯网络已经在专家系统、决策支持系统、数据挖掘系统和范例推理系统等许多重要领域产生应用价值和经济效益。
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