本文關(guān)鍵詞： 粗糙推理空間 粗糙數(shù)據(jù)推理 上近似 樹(shù)型推理空間 內(nèi)涵精度 數(shù)據(jù)關(guān)聯(lián)　出處：《北京交通大學(xué)》2017年博士論文　論文類(lèi)型：學(xué)位論文

【摘要】：信息科學(xué)的研究涉及數(shù)據(jù)處理的各個(gè)方面,相關(guān)的工作促進(jìn)了方向的產(chǎn)生,成果的出現(xiàn)推進(jìn)了學(xué)科的發(fā)展。作為信息科學(xué)的研究課題或研究方向,數(shù)據(jù)分類(lèi)、數(shù)據(jù)約簡(jiǎn)、數(shù)據(jù)倉(cāng)儲(chǔ)、數(shù)據(jù)篩選、數(shù)據(jù)挖掘、數(shù)據(jù)推演等針對(duì)數(shù)據(jù)處理的課題既表明了研究領(lǐng)域的寬泛與活躍,也蘊(yùn)含了理論和應(yīng)用相結(jié)合的研究理念。不同的工作雖各有側(cè)重,但常常涉及共同的研究層面。就數(shù)據(jù)問(wèn)題而言,不明確、非確定、似存在或潛存于數(shù)據(jù)之間的數(shù)據(jù)聯(lián)系與這些方向無(wú)不相關(guān),同時(shí)又在實(shí)際當(dāng)中頻繁出現(xiàn),從而引出了粗糙數(shù)據(jù)聯(lián)系的概念。對(duì)此的思考和關(guān)注促成了粗糙數(shù)據(jù)推理課題的產(chǎn)生,較少的涉足預(yù)示著研究的意義和前沿,加之理論研究將提供算法構(gòu)建的依據(jù)以及程序設(shè)計(jì)的基礎(chǔ)。因此本文聚焦于粗糙數(shù)據(jù)推理課題的研究,完成的工作集中于如下幾個(gè)方面:對(duì)粗糙集依托的近似空間進(jìn)行了結(jié)構(gòu)上的擴(kuò)充,引入了推理關(guān)系,產(chǎn)生了粗糙數(shù)據(jù)推理得以實(shí)施的依托環(huán)境—粗糙推理空間。為對(duì)粗糙數(shù)據(jù)聯(lián)系進(jìn)行描述,在粗糙推理空間中,通過(guò)等價(jià)關(guān)系與推理關(guān)系融合信息的上近似,引出了粗糙數(shù)據(jù)推理的定義,使推理運(yùn)作于數(shù)據(jù)之間,產(chǎn)生了課題研究的主題。經(jīng)對(duì)粗糙數(shù)據(jù)推理的研究,獲得了相關(guān)的結(jié)論,展示了粗糙數(shù)據(jù)推理的性質(zhì),包括:粗糙數(shù)據(jù)推理保持確定數(shù)據(jù)聯(lián)系的特性,粗糙數(shù)據(jù)推理與上近似中近似信息密切相關(guān)的特性,粗糙數(shù)據(jù)推理具有近似描述功能的特性,粗糙數(shù)據(jù)推理與路徑相互等價(jià)的特性,粗糙數(shù)據(jù)推理對(duì)應(yīng)不同等價(jià)關(guān)系的特性等。構(gòu)建了實(shí)際問(wèn)題的粗糙推理空間,描述了汽車(chē)制造產(chǎn)業(yè)鏈上企業(yè)以不同方式的分類(lèi),以及企業(yè)之間供貨鏈的確定信息。在該空間中,粗糙數(shù)據(jù)推理的推演刻畫(huà)了企業(yè)之間潛在供貨渠道的粗糙數(shù)據(jù)聯(lián)系,提供了智能處理和自動(dòng)管理的參閱信息,使粗糙數(shù)據(jù)推理的理論方法在實(shí)際中得到了的應(yīng)用。討論了特殊的粗糙推理空間—樹(shù)型推理空間中的粗糙數(shù)據(jù)推理,展示了以樹(shù)作為推理關(guān)系的特點(diǎn)。在樹(shù)型推理空間中,利用樹(shù)包含的層次信息,證明了以樹(shù)作為推理關(guān)系的重要結(jié)論:粗糙數(shù)據(jù)推理的推演依賴(lài)于數(shù)據(jù)位于的層次。由此通過(guò)對(duì)樹(shù)型推理空間的細(xì)化,展示了細(xì)化粗糙數(shù)據(jù)推理更趨于精確信息的推理特性。同時(shí)細(xì)化粗糙數(shù)據(jù)推理的結(jié)論可用于汽車(chē)制造產(chǎn)業(yè)鏈上供貨依賴(lài)關(guān)系的分析,使理論方法進(jìn)一步得到了應(yīng)用。在粗糙推理推理空間中給出了粗糙路徑的概念,證明了粗糙路徑與粗糙數(shù)據(jù)推理之間的相互對(duì)應(yīng)聯(lián)系,從而使粗糙路徑用于了粗糙數(shù)據(jù)推理內(nèi)涵精度的描述,由此區(qū)分了相同形式粗糙數(shù)據(jù)推理的相異內(nèi)涵,形成了對(duì)粗糙數(shù)據(jù)聯(lián)系松散或緊密程度的辨別方法,對(duì)于實(shí)際應(yīng)用具有指導(dǎo)性的作用。通過(guò)結(jié)構(gòu)化的�；瘶�(shù)構(gòu)建,并利用�；瘶�(shù)中的層次信息,給出了數(shù)據(jù)關(guān)聯(lián)的定義,產(chǎn)生了粗糙數(shù)據(jù)推理的關(guān)聯(lián)推理方法。該方法以關(guān)聯(lián)數(shù)據(jù)作為橋梁,結(jié)合數(shù)據(jù)的等同、等同的更接近、數(shù)據(jù)關(guān)聯(lián)的形式、關(guān)聯(lián)情況的數(shù)值表示、關(guān)聯(lián)程度的極大性處理等,使兩數(shù)據(jù)類(lèi)中的數(shù)據(jù)建立起了關(guān)聯(lián)關(guān)系,并以上近似的特定運(yùn)算作為數(shù)據(jù)關(guān)聯(lián)判定的充要條件。該方法的特點(diǎn)體現(xiàn)了對(duì)粒化樹(shù)中粒的層次和粒度變化的應(yīng)用,以及對(duì)數(shù)據(jù)關(guān)聯(lián)和關(guān)聯(lián)程度數(shù)值表示的處理。同時(shí)討論與實(shí)際問(wèn)題密切相關(guān),基于粒化樹(shù)的數(shù)據(jù)關(guān)聯(lián)方法用于了具體問(wèn)題的描述,實(shí)現(xiàn)了理論聯(lián)系于實(shí)際的研究預(yù)期。上述工作以粗糙數(shù)據(jù)推理作為研究的主體,以數(shù)據(jù)關(guān)聯(lián)推理作為研究的部分。探究步驟循序漸進(jìn),研究細(xì)節(jié)追求清晰、問(wèn)題分析逐步推進(jìn)、整體討論圍繞主題。這些工作包含了課題研究的自身方法,體現(xiàn)了對(duì)粗糙數(shù)據(jù)推理課題與數(shù)據(jù)關(guān)聯(lián)現(xiàn)象的理解與認(rèn)識(shí),形成了程序設(shè)計(jì)的算法基礎(chǔ)。同時(shí)針對(duì)實(shí)際問(wèn)題的模型刻畫(huà)和實(shí)際數(shù)據(jù)聯(lián)系的粗糙數(shù)據(jù)推理描述,展示了理論方法源于實(shí)際,實(shí)際應(yīng)用基于理論的研究目的。
[Abstract]:Study on information science involves all aspects of data processing, the related work to promote the direction of production, the results appear to promote the development of the discipline. As the direction of information science research or research data classification, data reduction, data warehousing, data filtering, data mining, data deduction for data processing program show the broad and active research field, but also contains the research concept of combining theory and application. Although different jobs have different emphases, but often involves the research level in common. Data is concerned, is not clear, uncertain, like the presence or potential data between the data associated with these directions are related at the same time, also appeared frequently in practice, which leads to the concept of rough data link. Thinking about this contributed to the rough data reasoning topic, less involved in the study indicates The significance and the frontier, and the theory research will provide the basis algorithm and program design based on rough data reasoning. This thesis focuses on the topic, complete the work focused on the following aspects: to rely on rough set approximation space was expanded on the structure, the reasoning relation, produced rough data reasoning to the implementation of the environment space. Relying on the rough reasoning described for connection to the data in the rough, rough reasoning space, approximate information fusion by equivalence relation and inference relation, leads to a rough number according to the definition of the reasoning, reasoning on data, the research topic. The research of rough data the reasoning, obtained the relevant conclusions, showing the nature of rough data reasoning including rough data reasoning keep determine characteristics of data relationship, rough data and reasoning On the approximate approximation characteristics is closely related to information, rough data reasoning has the characteristics of approximate description of function, characteristics of rough data reasoning and path are equivalent, rough data reasoning corresponding to different equivalence relation properties. Construct the rough reasoning of spatial problems, describes the automobile manufacturing industry chain enterprises to classification in different ways. And between the enterprise supply information to determine the chain. In the space, rough data of deduction depicts contact rough data between enterprise potential supply channels, providing intelligent processing and automatic management of the information, the application of theory and method of rough data reasoning has been discussed in practice. The special space rough reasoning tree type inference in space rough data reasoning, show the tree as inference tree inference relations. In space, the tree contains level The information proved to the tree as an important conclusion: the rough data reasoning of deduction depends on the data in the hierarchy. Thus through the refinement of the tree inference space, showing the characteristics of rough reasoning refinement data reasoning more accurate information. At the same time according to the number of refine the rough reasoning conclusion can be used for the analysis of automobile manufacturing industry chain supply dependency, the theory and method of further application. In the rough reasoning space gives the concept of rough path, proving the corresponding relation between the rough path and rough data reasoning, so that the rough path for the rough data reasoning connotation is described, which distinguishes the different connotation of the same form of rough data the reasoning, formed a discrimination method of rough data or loosely connected closely, is of great significance for practical application through the node. The grain tree construction, and using level of information granulation in the tree, gives the definition of data association, the association reasoning method of rough data reasoning. This method with associated data as a bridge to combine data equivalent, equivalent closer, data association, said the numerical Association. The correlation degree of maximal processing, so that the two data type of data to establish the relationship, necessary and sufficient conditions for a specific operation and above as approximate data association judgment. The characteristic of this method reflects the application of grain in grain and grain tree level changes, and the processing of numerical data association and said the association degree. At the same time discuss closely related problems, data association method for granulation tree based on specific description of the problem, the research realizes the connection of theory to actual expectations. The above work based on rough data reasoning As the research subject to data association reasoning as the research part. On a step by step, study the details of the pursuit of clear, problem analysis step by step, the overall discussion around the theme. The work includes research of its method, reflects the understanding and awareness of the rough data reasoning and data association problem phenomenon, forming algorithm based program design. Describe the rough data model to describe the relation reasoning according to practical problems and actual data, showing the theory stems from the practical application, the purpose of the study is based on the theory.

【學(xué)位授予單位】：北京交通大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2017
【分類(lèi)號(hào)】：TP18
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本文編號(hào)：1462218