【摘要】：為科學(xué)合理、精準(zhǔn)地對(duì)鐵路潛在關(guān)鍵風(fēng)險(xiǎn)源進(jìn)行定位管控,針對(duì)復(fù)雜事故鏈情境下的潛在風(fēng)險(xiǎn)關(guān)聯(lián)推理問(wèn)題,提出基于事故鏈情境本體建模的知識(shí)推理方法。首先在分析事故鏈案例情境要素的基礎(chǔ)上,解析事故致因機(jī)理;其次構(gòu)建基于本體的事故風(fēng)險(xiǎn)源知識(shí)模型,并建立事故風(fēng)險(xiǎn)源知識(shí)庫(kù);之后基于由知識(shí)關(guān)聯(lián)分析獲取的風(fēng)險(xiǎn)源關(guān)聯(lián)推理規(guī)則,采用Apriori算法對(duì)隱患庫(kù)進(jìn)行關(guān)聯(lián)分析,并將所得關(guān)聯(lián)規(guī)則重新導(dǎo)入事故風(fēng)險(xiǎn)源知識(shí)庫(kù),以實(shí)現(xiàn)知識(shí)庫(kù)的自學(xué)習(xí)與自更正;最后通過(guò)以地點(diǎn)為關(guān)鍵索引的事故鏈實(shí)例分析,驗(yàn)證方法的合理性和有效性,為精細(xì)化鐵路風(fēng)險(xiǎn)預(yù)控提供參考。
[Abstract]:In order to locate and control railway potential key risk sources scientifically and accurately, a knowledge reasoning method based on situational ontology modeling of accident chain is proposed to solve the problem of potential risk association reasoning in complex accident chain. Firstly, on the basis of analyzing the situational factors of accident chain cases, the mechanism of accident cause is analyzed, secondly, the knowledge model of accident risk source based on ontology is constructed, and the knowledge base of accident risk source is established. Then, based on the inference rules of risk source association obtained from knowledge association analysis, the hidden trouble database is analyzed by Apriori algorithm, and the association rules are reimported into the accident risk source knowledge base to realize the self-learning and self-correction of the knowledge base. Finally, the rationality and validity of the method are verified by an example of the accident chain with the key index of location, which provides a reference for the precise railway risk pre-control.
【作者單位】： 北京交通大學(xué)經(jīng)濟(jì)管理學(xué)院;
【基金】：國(guó)家自然科學(xué)基金(51278030) 北京交通大學(xué)科研基金(2017YJS080)
【分類(lèi)號(hào)】：U298

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