【正文】 式化；將不明顯的原理明顯化；將特定領(lǐng)域的特殊原理普遍化；將下意識(shí)的行為變成有意識(shí)的行為。它有著兩項(xiàng)特殊的任務(wù)：其一是從各個(gè)不同的領(lǐng)域中概括出它們的共性，不考慮它們低層次上的差異，從而提煉出抽象的、高層次的、綜合的認(rèn)識(shí)；其二是將特定領(lǐng)域中隱含的結(jié)構(gòu)明確化，以期總結(jié)出獨(dú)立于具體領(lǐng)域的普遍原理。將粒計(jì)算作為一個(gè)獨(dú)立的學(xué)科研究可以防止這種不必要的重復(fù)勞動(dòng)。在過去的若干年中，許多學(xué)者對(duì)粒計(jì)算的具體模式和方法進(jìn)行了研究。其七是容忍性：通過使用不同信息粒度，粒計(jì)算可以容忍不確定、不完全或有噪音的信息，從而獲得具有魯棒性的解決方案。其六是經(jīng)濟(jì)性：粒計(jì)算尋求在不同粒度上的近似解。其五是有效性：用粒計(jì)算指導(dǎo)的思維模式和行為方式將復(fù)雜問題分解成若干小問題。在抽象過程中，可以只重視主要特性而忽略不相關(guān)的細(xì)節(jié)，從而達(dá)到對(duì)問題的簡化。作為一個(gè)整體，粒計(jì)算提供的思維模式和行為方式是系統(tǒng)的、完整的。因而粒計(jì)算的結(jié)構(gòu)和現(xiàn)實(shí)世界的結(jié)構(gòu)、人們的思維模式及行為方式是一致的。因果推理是找出原因與結(jié)果之間的必然聯(lián)系。?；菍⒁粋€(gè)整體分割成部分，每個(gè)部分是擁有相同、相似性質(zhì)的個(gè)體的集合。因此，人們對(duì)現(xiàn)實(shí)世界的感知、理解、解釋和表示也是有結(jié)構(gòu)、分層次的。研究粒計(jì)算有許多原因。人們對(duì)粒計(jì)算的描述是建立在對(duì)它的直覺認(rèn)識(shí)上的：粒計(jì)算是研究基于多層次粒結(jié)構(gòu)的思維方法、問題求解方法、信息處理模式及其相關(guān)理論、技術(shù)和工具的學(xué)科。諸多國內(nèi)外學(xué)者就粒計(jì)算的基本理論和方法做了大量的工作[212]。 Classification目 錄目 錄摘 要 IABSTRACT III目 錄 V第一章 緒 論 1 1 1 2 2 5 6 6 7 目標(biāo)、方法和主要內(nèi)容以及創(chuàng)新點(diǎn) 8 8 8 9 9第二章 粒計(jì)算的獨(dú)特魅力 11 ——以孤立點(diǎn)挖掘?yàn)槔?11 11 12 12 13 15第三章 覆蓋粒計(jì)算在基于粗糙集的動(dòng)態(tài)信息系統(tǒng)規(guī)則挖掘中的應(yīng)用 17 17 17 19 19 20 22 24第四章 基于覆蓋粒計(jì)算的關(guān)聯(lián)沖突分析 26 26 27 27 29 30 30 37 39第五章 基于覆蓋粒計(jì)算的分類準(zhǔn)確性研究 40 40 41 42 42 44 45 47 50第六章 總結(jié)與展望 52 52 53參考文獻(xiàn) 54攻讀碩士學(xué)位期間取得的研究成果 61致 謝 62浙江師范大學(xué)學(xué)位論文獨(dú)創(chuàng)性聲明 63學(xué)位論文使用授權(quán)聲明 63第一章 緒 論第一章 緒 論 粒計(jì)算（Granular Computing, GrC）是一門飛速發(fā)展的新學(xué)科，[1]。 Rules Mining。 Covering。以上研究工作是覆蓋廣義粗糙集的理論及其應(yīng)用的補(bǔ)充和發(fā)展，充分的體現(xiàn)出了粒計(jì)算背景下知識(shí)發(fā)現(xiàn)理論和方法的獨(dú)特性，具有重要的理論意義及潛在的應(yīng)用價(jià)值。在粒計(jì)算的思維體系背景下，以實(shí)例輔證，給出了獨(dú)立于數(shù)據(jù)標(biāo)簽和不同理想分類結(jié)果假設(shè)（一種假設(shè)為劃分，另一種假設(shè)為覆蓋）的評(píng)價(jià)分類法準(zhǔn)確性的統(tǒng)一范式，為提高和評(píng)估分類法準(zhǔn)確性的計(jì)算提供了重要的參考意義。利用覆蓋沖突分析策略,通過“服務(wù)—資源”實(shí)例建立了關(guān)聯(lián)沖突分析的合理泛化模型，討論了關(guān)聯(lián)沖突過程中所可能引發(fā)異常的階段，并對(duì)不同階段引發(fā)的異常進(jìn)行了詳細(xì)的分析，給出了具體的解決方案,從而完善了各個(gè)領(lǐng)域沖突的解決。實(shí)驗(yàn)結(jié)果表明，在保持時(shí)間復(fù)雜度不變的情況下，利用改進(jìn)的規(guī)則挖掘算法，通過消除不一致因素而獲得的規(guī)則能更全面和更大程度地反映條件屬性值變化與決策變化趨勢(shì)之間的內(nèi)在聯(lián)系。因此，本文的主要內(nèi)容是在粒計(jì)算思想理論背景下，研究與覆蓋相關(guān)的理論及其應(yīng)用。粗糙集作為粒計(jì)算的一個(gè)重要分支，在理論和應(yīng)用上不斷取得豐碩成果的同時(shí)，也得到了廣泛有意義的推廣。學(xué)校代碼 10345 研究類型 應(yīng)用基礎(chǔ)研究碩 士 學(xué) 位 論 文 題 目: 覆蓋粒計(jì)算及其應(yīng)用研究 Research on the Covering and Its Application Based on Granular Computing Research on the Covering and Its ApplicationBased on Granular ComputingThesis Submitted toZhejiang Normal Universityfor the degree ofMaster of EngineeringByShuang Liu(Computer Software and Theory)Thesis Supervisor: Professor Jiyi WangJune, 2011摘 要覆蓋粒計(jì)算及其應(yīng)用研究摘 要粒計(jì)算是研究基于多層次粒結(jié)構(gòu)的思維方法、問題求解方法、信息處理模式及其相關(guān)理論、技術(shù)和工具的學(xué)科。它覆蓋了所有和粒度相關(guān)的理論、方法和技術(shù)，主要用于對(duì)不確定、不準(zhǔn)確、不完整信息的處理，對(duì)大規(guī)模海量的數(shù)據(jù)和對(duì)復(fù)雜問題的求解。而覆蓋廣義粗糙集理論是Pawlak粗糙集理論在劃分基礎(chǔ)上推廣到覆蓋建立起來的，它是研究與覆蓋相關(guān)的理論體系及其應(yīng)用，由于它是在粗糙集理論上的關(guān)系推廣，有關(guān)粗糙集的一些理論和應(yīng)用并不一定在覆蓋廣義粗糙集下適用。具體研究工作如下：一、在面向基于粗糙集理論的動(dòng)態(tài)信息系統(tǒng)規(guī)則挖掘的研究中，利用覆蓋粒計(jì)算相關(guān)理論提出了一種能消除引起差異信息系統(tǒng)規(guī)則挖掘中不一致因素的公理化方法。二、在面向沖突分析的研究中，在粒計(jì)算思想理論背景下，首次提出了“關(guān)聯(lián)沖突”的概念。三、在面向分類法準(zhǔn)確性（單標(biāo)簽和多標(biāo)簽數(shù)據(jù)集）的研究中，利用拓?fù)涓采w鄰域理論，給出了尋找覆蓋系統(tǒng)上重疊元素的相關(guān)公理化方法。最后，文章是在同一個(gè)思想理論背景下，討論了基于覆蓋的相關(guān)理論和應(yīng)用。 關(guān)鍵詞：粒計(jì)算；覆蓋；動(dòng)態(tài)信息系統(tǒng)；規(guī)則挖掘；關(guān)聯(lián)沖突；分類61ABSTRACTRESEARCH ON THE COVERING AND ITS APPLICATION BASED ON GRANULAR COMPUTINGABSTRACTGranular puting (GrC) is viewed as an interdisciplinary study of putation in nature, society and science, characterized by structured thinking, structured problem solving and structured information processing with an underlying notion of multiple levels of granulation. It consists of all the theories, methodologies, techniques and tools related to the granularity, which is mainly used to deal with uncertainty, imprecise and inplete information and seek resolutions from the largescale massive dataset or plicated problem. Rough set, as a very important branch of GrC, is being improving and perfecting on theory and application as well as is being extending widely and significantly. Generalized rough set on covering is the one that partition’s Pawlak rough set theory is extended into covering’s. It focuses on the study of covering, so that many theories and applications in the Pawlak rough set are not tenable and suitable in the generalized rough set on covering. Therefore, this dissertation will mainly make research on covering theories and its applications under background of GrC, whose content is shown as follows:First of all, for the rules mining based on rough set theory in dynamic information system, a preprocess approach to eliminate the elements that cause inconsistence of rules mining in difference information system is proposed under the background of covering theory based on granular puting. Experiment shows that relationship between the changes of condition attributes values and trend of decisionmaking can be fully reflected as much as possible by a modified rules mining algorithm under the same time plexity through this preprocess approach.Secondly, for the conflict analysis, associatedconflict is firstly introduced in the perspective of GrC, and a reasonable and prehensive approach to its analysis, using covering based on granular puting, is outlined. We argue that this model of associatedconflict analysis, given by the example of serviceresource, will provide more profound insight for the conflict resolution in different fields.Thirdly, for the accuracy of classification method on single label dataset or multi label dataset, a unified paradigm for the accuracy used to evaluate different classification methods, using topological covering based on GrC, is presented, independent on number of data labels and different assumptions of ideal classification result(one assumption is partition, the other is covering). And some corresponding examples are also discussed to illustrate the accuracy in different classification situations. This unified paradigm will provide important reference value for the evaluation and improvement of accuracy of classification method.In brief, this paper discusses theories and applications related to the covering under the same theory background, and it can be treated as supplement and development of generalized rough set on covering. And it reflects the specificity on theories, methodologies, techniques and tools of knowledge discovery under the background of GrC, with significant referred and applied value in the future. KEY WORDS: GrC。 Dynamic Inf