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yuzhe_999銀蟲(chóng) (小有名氣)
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[求助]
計(jì)算機(jī)方面論文英語(yǔ)摘要(不要google翻譯。
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形式概念分析是由德國(guó)Wille. R教授在1982年提出的,它基于形式背景來(lái)分析形式概念,是一種有效的知識(shí)獲取和數(shù)據(jù)分析的工具,其核心是概念格。形式背景作為一種特殊的信息系統(tǒng),是由對(duì)象和屬性組成的二值背景。目前,形式概念分析已被廣泛的研究,并成功應(yīng)用到機(jī)器學(xué)習(xí),軟件工程和信息獲取等領(lǐng)域。 屬性約簡(jiǎn)是數(shù)據(jù)挖掘理論研究的核心問(wèn)題之一。本文主要研究決策形式背景為不協(xié)調(diào)時(shí)如何進(jìn)行屬性約簡(jiǎn),同時(shí)這種約簡(jiǎn)方法(近似約簡(jiǎn))如何在電力系統(tǒng)故障診斷時(shí)運(yùn)用。主要內(nèi)容如下: (1)研究了決策形式背景為不協(xié)調(diào)時(shí)如何進(jìn)行屬性約簡(jiǎn)的問(wèn)題。其中首先定義了下近似協(xié)調(diào)集、決策約簡(jiǎn)集等;然后又提出了下近似協(xié)調(diào)集和決策約簡(jiǎn)集的判別方法;之后又構(gòu)造了可辨識(shí)屬性集和可辨識(shí)屬性矩陣;最后給出了近似約簡(jiǎn)方法同時(shí)用實(shí)例驗(yàn)證了本文中的約簡(jiǎn)方法。 (2)在電力系統(tǒng)故障診斷中使用了近似約簡(jiǎn)方法來(lái)提取決策規(guī)則。給出了故障診斷決策形式背景和故障診斷決策規(guī)則的置信度的定義,用近似約簡(jiǎn)方法對(duì)某電力系統(tǒng)的故障決策形式背景進(jìn)行了約簡(jiǎn),最終得出了帶有置信度的故障診斷決策規(guī)則,這樣有助于運(yùn)行人員在故障發(fā)生時(shí)根據(jù)決策規(guī)則來(lái)判斷故障元件的可能出處(或區(qū)域),以便及時(shí)準(zhǔn)確地修復(fù)故障。 關(guān)鍵詞:不協(xié)調(diào)決策形式背景;屬性約簡(jiǎn);電力系統(tǒng)故障 |
榮譽(yù)版主 (知名作家)
笑熬漿糊——滿腦漿糊
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Formal concept analysis, which is proposed by Prof. Wille. R from Germanbased on formal context in 1982, is an effective knowledge acquisition and data analysis tool with a core of concept lattice. Form of background was used as a special information system, which is composed of double-value background: objects and attributes. At present, the formal concept analysis has been extensively investigated, and successfully applied to the field of machine learning, software engineering and information access. Attribute reduction is one of the core issue of data mining theory. This paper includes the decision of formal context on how to proceed the inconsistent attribute reduction, which (approximate reduction) could be used in power system fault diagnosis. The main contents of this paper are as follows: (1) the decision has been made towards the formal context for the inconsistent attribute reduction. The lower approximation consistent set of decision-making about Jane set was firstly defined. Then the lower approximation consistent set, and decision-making reduction set discrimination method were proposed, based on which a recognizable set of attributes and the discernibility matrix were constructed; Finally, the examples were demonstrated by the approximate reduction method. (2) The decision rules has been extracted by using this approximate reduction in the power system fault diagnosis method. The confidence on decision-making rules of formal context of fault diagnosis and diagnosis were defined. With the help of approximate reduction method, the fault reduction for the background of the decision-making in the form of a power system was concluded. In fact, the fault diagnosis decision-making with confidence rules could help to run in accordance with the decision-making rules to determine the possible source of the fault element (or regional) failure to timely and accurate repair when a fault occurs. Keywords: background of the form of inconsistent decision; attribute reduction; power system fault. |

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