本文選題：模糊認知圖 + 知識元�。� 參考：《大連理工大學》2015年碩士論文

【摘要】：案例推理可以根據(jù)以往經(jīng)驗為突發(fā)事件的應急管理提供決策輔助,當前案例推理的相關研究中大致可以歸為兩類,其中最主流的方法是基于案例推理的方法(CBR),大量學者從案例屬性、特征的角度出發(fā)提出了案例結構表示、案例檢索匹配方法等,對CBR方法做了眾多的改進型研究。另外,有部分學者嘗試著從案例的內(nèi)容出發(fā),針對特定領域內(nèi)的應急突發(fā)事件的結果進行模擬或預測。這兩類方法普遍存在的問題有：一是現(xiàn)有CBR類方法從案例屬性、案例特征的角度出發(fā)通過類比推理的思想來解決問題,須要人為定義案例結構及案例表示方法,從而導致領域概念、案例結構無法統(tǒng)一表示；二是現(xiàn)有基于案例內(nèi)容的推理方法處于探索階段且相關研究相對較少,其推理過程相對簡單,推理結果需要專家參與解釋；另外,現(xiàn)有兩類方法缺乏對事件要素間的隱性知識和應急突發(fā)事件的發(fā)展過程的研究,且人為影響因素占比很大導致推理結果缺乏客觀性。針對上述局限,本文以應急案例作為研究對象,通過挖掘事件要素間的關聯(lián)信息和因果知識來構建模糊認知圖(FCM)從而進行案例推理。首先,通過文本挖掘的方法獲取應急案例中的領域概念知識元,利用關聯(lián)分析方法抽取領域知識元間內(nèi)在的聯(lián)系,挖掘領域概念間的隱性知識,即事件要素間的因果關聯(lián)知識；然后,根據(jù)所獲取到的領域知識元間的因果關聯(lián)知識來識別FCM結構的節(jié)點及節(jié)點間的影響權重,從而構建了應急案例的模糊認知圖推理模型,通過連接事件要素來統(tǒng)一表示案例結構及領域概念,并分析了應急案例FCM的推理過程及結果；最后,選擇煤礦瓦斯類應急案例文本作為實驗對象,抽取瓦斯類應急案例的事件要素并挖掘出要素間的因果知識,利用本文模型構建了煤礦瓦斯類應急突發(fā)事件的FCM推理模型,推理結果證實了本文方法的實用性及可靠性。本研究提出了基于領域知識元的應急案例FCM推理模型有其優(yōu)勢：一是,從基于案例內(nèi)容的角度出發(fā),利用領域概念知識元作為應急案例FCM的節(jié)點可以表示出事件要素間內(nèi)在的因果知識,避免了人為影響因素過多的弊端,解決了現(xiàn)有方法從案例屬性、案例特征出發(fā)無法統(tǒng)一表示案例結構、領域概念的問題；二是,應急案例FCM推理模型的推理過程可以展示出整個事件的演化過程及各個事件要素的狀態(tài)變化過程,相比現(xiàn)有案例推理方法提高了案例推理的準確度和客觀性。另外,利用應急案例FCM推理模型可以為決策者掌握事件發(fā)展狀態(tài)、預測事件結果、引導事件發(fā)展走向等提供決策依據(jù)。
[Abstract]:Case-based reasoning (CBR) can provide decision support for emergency management according to past experience. The most popular method is case-based reasoning (CBR). A large number of scholars put forward case structure representation and case retrieval matching method from the point of view of case attributes and features. In addition, some scholars try to simulate or predict the results of emergency emergencies in a specific field. The common problems of these two methods are as follows: first, the existing CBR methods solve the problems by analogy reasoning from the view of case attributes and case characteristics, and need to define the case structure and case representation methods artificially. As a result, the domain concept and case structure can not be uniformly represented; second, the existing case-based reasoning methods are in the exploratory stage and the relative research is relatively few, the reasoning process is relatively simple, and the reasoning results need experts to participate in the interpretation; in addition, There is a lack of research on the tacit knowledge between the elements of events and the development process of emergency emergencies, and the large proportion of human factors leads to the lack of objectivity of reasoning results. In view of the above limitations, this paper takes emergency cases as the research object, and constructs fuzzy cognitive map (FCM) by mining the correlation information and causality knowledge between event elements to carry out case-based reasoning. Firstly, the domain concept knowledge element in emergency case is acquired by text mining method, and the intrinsic relation between domain knowledge element is extracted by association analysis method, and the tacit knowledge among domain concepts is mined, that is, causal association knowledge between event elements. Then, according to the knowledge of causality relation between domain knowledge elements, the nodes of FCM structure and their influence weights are identified, and the fuzzy cognitive graph reasoning model of emergency case is constructed. The case structure and domain concept are unified by connecting event elements, and the reasoning process and results of emergency case FCM are analyzed. Finally, the text of coal mine gas emergency case is selected as the experimental object. This paper extracts the event elements of gas emergency cases and excavates the causality knowledge between them. The FCM reasoning model of coal mine gas emergency emergencies is constructed by using the model of this paper. The result of reasoning proves the practicability and reliability of the method in this paper. In this study, the FCM reasoning model based on domain knowledge element has its advantages: first, from the perspective of case-based content, Using domain concept knowledge element as the node of emergency case FCM can express the inherent causality knowledge among the elements of the event, avoid the malpractice of too many human factors, and solve the existing method from the case attribute. The problem of case structure and domain concept can not be represented by case characteristics. Second, the reasoning process of emergency case FCM reasoning model can show the evolution process of the whole event and the state change process of each event element. Compared with the existing Case-Based reasoning (CBR), the accuracy and objectivity of Case-Based reasoning (CBR) are improved. In addition, the emergency case FCM reasoning model can provide decision basis for decision-makers to grasp the state of event development, predict the outcome of events, and guide the development of events.
【學位授予單位】：大連理工大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：D035.2

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