hidden attribute 中文意思是什麼
hidden attribute
解釋
隱藏特性-
A named attribute of a control, field, or database object that you set to define one of the object s characteristics, such as size, color, or screen location ; or an aspect of its behavior, such as whether it is hidden
平展行集（ flattened rowset ）表現為二維行集的多維數據集，其中多個維度的元素的唯一組合在一個軸上進行組合。有關詳細信息，請參閱ole db文檔。 -
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。 -
Abstract : with the modification of intersection point attribute and application of the depth data about graphic, it defines the vertex properties and puts forward a hidden method oriented to point distinguishing
文摘:應用圖形元素的深度值信息，並通過對交點屬性值的修改，確定被遮擋零件的頂點屬性，提出了方向點判別消隱法。 -
Multi - rules neural network learning part decreases the dimensions of attribute collection, to reach the goal of simplifying the input ; we stress the multi - rules learning algorithm based on fuzzy entropy rule ; at the same time, all the knowledge available is used to design the input layer, hidden layer and output layer of the neural network
多準則神經網路部分對客戶屬性集進行維數約簡，重點介紹了以模糊熵準則為基礎的多準則學習方法，同時提出了網路輸入層、隱含層及輸出層的構造方法。
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