隱約的知識 的英文怎麼說
中文拼音 [yǐnyāodezhīzhì]
隱約的知識
英文
ore of the loom- 隱 : Ⅰ動詞(隱瞞; 隱藏) hide; conceal Ⅱ形容詞1 (隱藏不露) hidden from view; concealed 2 (潛伏的; ...
- 約 : 約動詞[口語] (用秤稱) weigh
- 的 : 4次方是 The fourth power of 2 is direction
- 知 : Ⅰ動詞1 (知道) know; realize; be aware of 2 (使知道) inform; notify; tell 3 (舊指主管) admin...
- 識 : 識Ⅰ動詞[書面語] (記) remember; commit to memory Ⅱ名詞1. [書面語] (記號) mark; sign 2. (姓氏) a surname
- 隱約 : indistinct; faint
- 知識 : 1 (認識和經驗的總和) knowledge; know how; science 2 (有關學術文化的) pertaining to learning o...
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Using the statistic characterization of data, the relevant knowledge reduction algorithm is put forward by combining the probability with classification rules ; using the characterization of fuzzy attributes, the decision system with subjection degree attribute is built by combing the rough set theory and fuzzy set theory, and the idea of distinguish matrix is induced to the concealed decision system to reduce data
利用數據的統計特徵,將概率測度與分類規則結合起來,提出了相應的知識西北工業大學博士學位論文約減演算法;利用模糊屬性集合的特點,把粗糙集合與模糊集合有機結合起來,將粗糙集中分辨矩陣的思想引入到具有隸屬度屬性的隱式決策系統中進行數據約減。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。This thesis discusses the theoretical models and some key techniques of information hiding in digital images. in this thesis, we attempt to establish a theoretical framework for image information hiding. at fist, a modification of a simmon ' s " prisoners " problem is proposed to admit typcal image information hiding scenarios
通過考察圖象信息隱藏與攻擊的典型應用場景,從發信方和收信方的知識約束、隱寫密鑰管理、收信方的行為模式和攻擊方的行為約束等幾方面對simmons提出的「囚犯問題」進行擴充,提出了一個擴展的理論模型。
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