精度粗糙集 的英文怎麼說

中文拼音 [jīngdùcūcāojí]
精度粗糙集 英文
vprs
  • 精 : Ⅰ形容詞1 （經過提煉或挑選的） refined; picked; choice 2 （完美;最好） perfect; excellent 3 （細）...
  • 度 : 度動詞[書面語] （推測; 估計） surmise; estimate
  • 粗 : Ⅰ形容詞1 （長條東西直徑大的） wide （in diameter）; thick 2 （長條東西兩長邊的距離寬的） wide （i...
  • 糙 : 形容詞（粗糙; 不細致） rough; coarse; crude
  • 集 : gatherassemblecollect
  • 精度 : precision; accuracy; degree of accuracy; precision accuracy; trueness
  • 粗糙 : （不精細; 不光滑; 不細致; 草率） coarse; rough; crude
  1. With the rough sets theory, people can process the undistinguished problem using uncompleted information or knowledge. and also enhance the capability to classify the imprecise data coming from observation or measurement

    粗糙集理論反映了人們以不完全信息或知識去處理一些不可分辨現象的能力，或依據觀察、度量得到某些不精確的結果而進行數據分類的能力。
  2. In some projects charged by our lab such as national 863 project - " crop planting management components based on weather analyse ", anhui provincial 95 key project - " agricultural meteorology disaster evaluation system base on gis in anhui province " and the project " small coal mine security management and decision system based on gis in anhui province ", this paper combines the theory and arithmetic of rough set with gis and data mining in idss, investiges the application of rough set theory to precision analysis of attribute data and logical operation in gis, analyzes the logical operation based on rough set ( logical union, logical intersection, logical complement, mixed logical operation etc. ), so that it can give a method y to research the gis attribute data and the uncertainty of attribute data after superposition operator, so as to express the roughness and illegibility of attribute data more accurately

    在完成試驗室所承擔的國家863項目「基於氣象分析的農作物種植管理軟構件」 、省95攻關項目「基於gis的安徽省重大農業氣象災害測評系統」和「基於gis的安徽省小煤礦安全管理決策系統」等項目中，將粗糙集理論和演算法與gis 、智能決策系統中的知識發現等相結合，對粗糙集理論在gis屬性數據和邏輯運算精度分析中的應用情況進行了研究，分析了基於粗集的gis邏輯運算（邏輯並、邏輯交、邏輯補、混合邏輯等） ，從而為研究gis屬性數據及其疊加運算后屬性數據的不確定性提供了一種方法，能比較準確地表達屬性數據的模糊性和粗糙性。
  3. Variable precision rough set model based on general relations

    一般關系下的變精度粗糙集模型
  4. Choice of parameter based on vprs with asymmetric bounds

    基於不對稱邊界的變精度粗糙集的參數選擇
  5. Method of machinery fault diagnosis based on variable precision rough set

    基於變精度粗糙集的機械故障診斷方法
  6. In this chapter, we bring forward a variable precision rough set model

    在不完備信息系統下的粗糙集理論擴充方面，本文提出了一種變精度粗糙集模型。
  7. In chapter 3, the relationship, combination and unification of graded rough sets and variable rough sets are researched

    第三章，研究了程度粗糙集和變精度粗糙集兩種廣義粗糙集模型的性質、關系和統一。
  8. In this paper, the mathematical foundation study of rough sets and the study of two general rough sets models are mainly researched

    本文主要進行了粗糙集的數學基礎研究，與程度粗糙集和變精度粗糙集兩個廣義粗糙集模型的探討。
  9. 11 mounlinier i, ganascia j g. applying an existing machine learning algorithm to text categorization. in connectionist statistical, and symbolic approaches to learning for natural language processing, wermter s, riloff e, scheler g eds., heidelberg, germany : springer verlag, lecture notes in computer science, vol

    由於挖掘出的特徵項目集可能很多，為了進一步的精簡項目集，提出了一個以可變精度粗糙集模型為基礎的方法對每個特徵頻繁項目集對分類的貢獻進行評估，剪除那些對最後的分類效果貢獻不大的項目集，並用精簡后的項目集構造每類文檔的主題模板。
  10. The basic rough set theory is introduced in brief. the method of how to get the decision rules through the rough set and recent popular arithmetic methods are mentioned. finally, a real - life example is given to explain the basic notions and get the decision rules to illustration the problem

    3 .引入非參數式可變精度粗糙集模型，介紹一些基本的概念和性質，並給出證明;用分佈一致性方法來對多屬性決策問題進行多屬性約簡，引入相關的概念，並對所得到的性質和判定定理，給予理論上的證明，得出最後的決策步驟，並且最終獲得多屬性決策問題的決策規則。
  11. While putting rough set theory into practice, this thesis pays attention to setting - up the proper data structure. in order to improve the data utilization ratio and promote rule quality, this thesis puts forward the method of " divide equally and examine each other this thesis bring forward the method of dynamic reduce to overcome data noise and confirm the best reduction finally with the help of rosetta tool software we apply the above concept and method to reality, and succeeded in obtaining the optimum rule for the expert system of production scheduling in daye iron ore mine, wuhan iron and steel company

    由於標準粗糙集模型對數據噪音高度敏感以及工程應用中數據噪音引入的不可避免性，標準粗糙集模型在實際應用中存在一系列問題，為克服數據噪音以及規則泛化的需要，本文採用變精度模型，由此模型引入近似約簡方法。本文在將粗糙集理論及變精度粗糙集模型應用於實際的同時，注重研究了適當數據結構的建立。為提高數據利用率，提升規則生成的質量，提出了平分互測規則集泛化能力考核方法。
  12. Among these rough set models, non - parameter variable precision rough set model ( nvprs ), appeared to the improvement of variable precision rough set model ( vprs ) but really not, has been presented only for several years. this model, avoiding the choice of parameter, usually difficultly determined or not necessary used, could form the separated theory framework

    在這些模型之中，非參數式可變精度粗糙集模型是這幾年才提出來的，雖然它看似是可變精度粗糙集模型變型，但是卻有自身的特點，避開了參數的選擇的問題，而且自身可以形成一套適合自己的理論體系。
  13. We can prove from the result of experiment that the web text mining approach could be more efficient than other classification algorithms whatever in precision, recall rate, or in novelty of knowledge. moreover, the technology is language independence

    從實驗結果看，基於粗糙集的web文本分類演算法無論在分類精度、分類效率，還是知識的新穎程度方面，都比以往分類演算法有明顯提高；而且，這種技術是語言獨立的。
  14. Firstly, influence factors of generalization of neural network are presented in this thesis, in order to improve neural network ’ s generalization ability and dynamic knowledge acquirement adaptive ability, a structure auto - adaptive neural network new model based on genetic algorithm is proposed to optimize structure parameter of nn including hidden layer nodes, training epochs, initial weights, and so on ; secondly, through establishing integrating neural network and introducing data fusion technique, the integrality and precision of acquired knowledge is greatly improved. then aiming at the incompleteness and uncertainty problem consisting in the process of knowledge acquirement, knowledge acquirement method based on rough sets is explored to fulfill the rule extraction for intelligent diagnosis expert system, by completing missing value data and eliminating unnecessary attributes, discretization of continuous attribute, reducing redundancy, extracting rules in this thesis. finally, rough sets theory and neural network are combined to form rnn ( rough neural network ) model for acquiring knowledge, in which rough sets theory is employed to carry out some preprocessing and neural network is acted as one role of dynamic knowledge acquirement, and rnn can improve the speed and quality of knowledge acquirement greatly

    本文首先討論了影響神經網路的泛化能力的因素，提出了一種新的結構自適應神經網路學習演算法，在新方法中，採用了遺傳演算法對神經網路的結構參數（隱層節點數、訓練精度、初始權值）進行優化，大大提高了神經網路的泛化能力和知識動態獲取自適應能力;其次，構造集成神經網路，引入數據融合演算法，實現了基於集成神經網路的融合診斷，有效地提高了知識獲取的全面性、完善性及精度;然後，針對知識獲取過程中所存在的不確定性、不完備性等問題，探討了運用粗糙集理論的知識獲取方法，通過缺損數據補齊、連續數據的離散、沖突消除、冗餘信息約簡、知識規則抽取等一系列的演算法實現了智能診斷的知識規則獲取;最後，將粗糙集理論與神經網路相結合，研究了粗糙集-神經網路的知識獲取方法。
  15. By the application of the rough set theory, this paper makes quantized evaluation with the geological engineering model for slope, explains its establishing method and procedure, and presents a network for the recognition of the deformation and failure modes of slope. examples from practice are analyzed with the model, which concludes its advantages of high speed, precision, practicability and powerful quantization, exploring a new way for quantized model establishment for slope

    應用rs （ roughset或粗糙集）理論，對邊坡地質工程模型進行量化判別，闡述了rs邊坡地質工程模型的建模方法及實現步驟，提出了邊坡變形破壞模式的識別網路，進行了實例分析，結果表明該方法具有速度快、精度高、實用性強和量化功能強等優點，為邊坡量化建模提供了新的思路。
  16. Owing to the high sensitivity to noise data, the application of normal rough set model in engineering is restricted, this thesis put forward the method of " data set divided equally and examine each other " to improve data utilization ratie

    摘要普通粗糙集模型對數據噪音的高度敏感限制了其在工程實際中的應用，本文在變精度模型近似約簡的基礎上提出了數據全集隨機平分互測法以提高數據的利用率。
  17. Then, we use the interest recognition algorithm based on the concept tree model and the vprs model of the rough set theory to find user concept model, in order to recommend the service for the personalization of the website, we convert the concept model into user interest concept

    再利用基於粗糙集理論中的可變精度模型（ vprs ）的興趣識別演算法獲得用戶概念模式，並將其轉換為用戶的興趣概念樹，從而為網站的個性化推薦服務。最後，初步實現了一個個性化網站模塊的設計。
  18. In this paper, a rs - based model, which starts up from trained documents for web documents classification, is introduced. taking advantage of the rs theory ' s features in efficient dealing with vague, indiscernible, and fuzzy information, we sets up a series of layered subsystems to reduce redundant properties from classification tables. in this way, we can not only efficiently reduce the dimension of documents but also keep the information of keywords set

    本文提出了一種基於粗糙集理論的web文本分類模型，該模型從已分類的訓練文本出發，建立一系列不同層次的文本分類子系統，利用roughset理論有效處理不精確、不確定、含糊信息的特性，對分類決策表進行屬性約簡，既有效降低了web文本的維度，又保持關鍵詞集合中的信息。
  19. Because of the shortcomings of the classical rough sets model such as the sensitive to noise often encountered in many real - world applications, the dissertation presents a variable precision and md relation rough sets model from the perspective of rough membership function and micro - difference. not only can the vp - md model overcome the shortcomings of the classical model, but also is consistent with the statistics. this model can extend the application scopes of rough sets and enhance its adaptability

    本文從對象的不可分辨關系出發，討論了信息系統的經典粗糙集模型，並針對經典粗糙集模型存在的對噪音敏感等缺陷，提出了基於隸屬度和微差距離的可變精度微差關系（ vp - md ）模型，該模型不僅能夠處理含有噪音的不完全信息系統，其結果也能反映大量數據所滿足的統計規律，使粗糙集理論的應用范圍更廣、適應性更強。
  20. On the base of extend rough set theory, this paper put forward the improved data mining algorithm with priority attributes based on the priority relation. therefore, the classification precision of basic rough set and rough set with priority attributes reached unification and the classification rules by this model in the section are more curtail and rational. 4

    論文在粗糙集拓廣理論的基礎上，利用屬性的有序特性即優先二元關系，提出有序屬性的數據挖掘改進演算法，使基本粗糙集和帶有準則的粗糙集在挖掘分類精度上達到統一，且挖掘出的規則簡練、更具合理性和綜合性。
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