attribute extraction 中文意思是什麼

attribute extraction 解釋
屬性提取
  • attribute : vt. 1. 把（某事）歸因於…。2. 認為…系某人所為。n. 1. 屬性，特質。2. （人物、官職等的）標志，表徵。3. 【語法】屬性形容詞。
  • extraction : n. 1. 抽出，拔出。2. 【化學】提取（法）；萃取（法）；回收物，提出物；精煉。3. 精選，摘要。4. 血統，家世，出身。5. 【數學】開方，求根。
  1. In the implementation of data classifier, we describe extraction and management of conceptual hierarchy for data, also design an automatic extraction algorithm for numeric data. in this section, we still provide the two algorithms of concept - based attribute - oriented induction and evaluating classification scheme and the visualization of classification rule. finally, the data classifier is tested in databas the results show that it is practical and its performance meet the requirement of designing

    然後，在數據分類器的實現中，論述了數據的概念層次提取和管理，並對數值型數據給出了一個自動提取概念層次演算法；同時給出了基於面向屬性歸納的分類演算法、分類模式的評價演算法和分類規則的可視化方法。
  2. 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。
  3. The main steps are extracting and analyzing different types of attributes, preprocessing the extracted attributes, rejecting attribute anomalous values and filtering, seeking and selecting the sensitive attributes combined with drilling and oil extraction data, descending the optimal seismic attributes through k - l changes, and using the synthetic analysis technology with linearity and nonlinearity on reservoir prediction

    其主要步驟為：不同種類的屬性提取和分析；屬性的預處理，即剔除異常值並進行濾波等處理；結合鉆井、採油資料尋找和篩選敏感屬性；利用k - l變換來對優選出的地震屬性進行降維處理；利用線性、非線性等綜合分析技術進行儲層預測。
  4. Attribute extraction template file

    屬性提取樣板文件
  5. This paper concludes the following items : the mutual transform between the graphics data and attribute data of 3d model and database the theory of 3d modeling based on discrete algorithm and techniques dealing with bifurcation orebody the technique of model render based on opengl the theory and algorithm of model interaction and division according to these theories, the built model can be used to realize the visualization of production designing, extraction of slices in any orientation and production index calculations

    論文從工程應用的角度出發，主要進行了以下幾個方面的工作：三維模型的空間數據和屬性數據與數據庫的相互轉換基於離散演算法的三維建模原理和分歧礦體處理技術基於開放圖形庫（ opengl ）的模型渲染技術模型交互、剖切原理與演算法實現基於該原理和方法建立的三維模型可用來實現生產設計可視化、任意方位剖面的剖切、各種生產指標的精確計算等。
  6. The method system of reservoir geological modeling integrated seismic and well - log data is built. it includes the matching methods of well - log and seismic data, the methods of seismic attribute extraction and effectiveness analysis, the methods of reservoir structure modeling, and the methods of reservoir property modeling

    總結了地震與地質資料綜合儲層地質建模的方法體系，包括井震數據匹配方法、地震屬性提取與有效性分析方法、儲層結構模型建模方法和儲層屬性模型建模方法四部分內容。
  7. Attribute extraction file

    屬性提取文件
  8. Technique of attribute weights extraction in application specific instruction set processor design

    評估指標權重抽取技術
分享友人
分享到 Line

分享到臉書