rule of generalization 中文意思是什麼

rule of generalization 解釋
廣義化規則
  • rule : n 1 規則，規定；法則，定律；章程，規章；標準；（教會等的）教規，條例，教條；常例，慣例。2 統治，...
  • of : OF ＝Old French 古法語。
  • generalization : n. 1. 一般化，普遍化。2. 概括，綜合，總結；歸納；法則化。3. 廣義；概說；概念，通則。
  1. Their learning and training rules have been analyzed profoundly and their abilities to approximate arbitrary nonlinear function have been testified and compared by the simulation. a new rbf neural network has been presented which uses a raised - cosine function as activation transfer function. it provides a wider generalization in comparison with gaussian rbf neural networks by simulation as well as strong approximation ability, fast convergence, a rule to select the parameters of the networks

    本文詳細研究了兩種典型的前向神經網路（ bp網路和rbf網路）的學習和訓練演算法，提出了一種新穎的基於緊支集餘弦函數的徑向基神經網路，其克服了常用的高斯型rbf神經網路雖具有緊支集但各基函數非正交的不足，其收斂速度快、網路參數選取有理論依據且相比于高斯型rbf神經網路具有更強的泛化能力，模擬驗證了其有效性。
  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. In this paper, we firstly present the whole framework of the system, including the introduction of the main functional module. next, in the part of data preprocessing, we design a method of collecting click - stream data in the application server layer and preprocessing them with real time ; in the part of data mining that is data analyzing, we research and implement an extended attribute - oriented induction algorithm which applies to data generalization analysis, and that, we also design and implement an hybrid - dimensional association rule mining algorithm for associative analysis. in the end, on the e - business web site system of jiangsu changjiang electronic group corp, we design and implement an intelligent dss ( idss ) with the help of the above algorithms

    論文首先給出了系統的整體框架體系結構設計，以及主要的功能模塊介紹；接著，在數據預處理部分，設計了在應用層收集點擊流數據並且對其進行實時預處理的方法；在數據挖掘即數據分析部分，研究與實現了用於數據概化分析的面向屬性規約的擴展演算法，以及設計並實現了用於關連分析的混合維關聯規則挖掘演算法；最後，在江蘇長江電氣集團的電子商務網站系統上，利用已分析的演算法設計並實現了一個智能決策支持系統。
  4. The convergence of the pnn decision rule for the bayesian decision rule is proved with probability. an explicit formulation of pnn generalization ability is proposed. and the accuracy rate of a classification network is explained as the maximum likelihood estimation of the generalization ability

    證明了pnn的決策函數依概率收斂于貝葉斯決策函數;給出了pnn的推廣能力表達式;證明了一個分類網路的測試集正確率是該網路推廣能力的極大似然估計;給出了分類網路中需要的測試集數目表達式;證明了pnn推廣能力不大於由貝葉斯決策所帶來的正確識別率
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