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dynamic knowledge in Chinese

Pronunciation:
How to pronounce "dynamic knowledge""dynamic knowledge" in a sentence

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  • 動態(tài)知識

Examples

  • Evolutionary game of dynamic knowledge exchanging in knowledge interaction
    知識互動中的知識交換行為進化博弈分析
  • The effects of learner - generated diagrams on understanding and application of dynamic knowledge in explanatory text
    學習者生成圖解對說明文閱讀理解和應用的效果
  • Experimental results show that the construction of the dynamic knowledge is reasonable and the retrieval efficiency is improved
    初步測試結果表明，本系統(tǒng)建立的知識庫結構比較合理，在一定程度上改善了檢索精度。
  • The dynamic knowledge model with temporal and spatial characters for cotton management includes three modules as pre - sowing plan design , dynamic development indices , diagnosis and regulation
    具有時空適應性的棉花栽培管理動態(tài)知識模型主要包括播前方案設計、生育指標動態(tài)和苗情診斷調控知識模型三個部分。
  • Second , temporal logic is adopted to describe the temporal attributes of the static knowledge and the temporal relations , constraints of the dynamic knowledge , with which are dealt as isolated temporal knowledge
    二、采用時態(tài)邏輯描述靜態(tài)知識的時態(tài)屬性以及動態(tài)知識的時態(tài)關系和約束，把它們獨立出來作為時態(tài)知識進行處理。
  • Our experience shows that university - based businesses have a vital role to play in fostering a dynamic knowledge - based economy in ireland , that will provide sustained growth with more , and better , higher - value jobs in the future
    我們的經(jīng)驗告訴我們以大學為依托的經(jīng)濟實體對促進愛爾蘭知識經(jīng)濟的蓬勃發(fā)展起著至關重要的作用，促使了未來更多、更好、更有價值的工作機會的持續(xù)性的增長。
  • On the basis of these approaches , we discuss and implement dkirs ( dynamic knowledge base information retrieval system ) , which addresses these problems by carrying out the query expansion through dynamic knowledge
    本文在總結現(xiàn)在方法的基礎上，討論并實現(xiàn)了一個基于動態(tài)知識庫的全文信息檢索系統(tǒng)( dkirs ) ，本系統(tǒng)試圖通過自動構建的動態(tài)知識庫解決這兩類詞匯問題，在一定程度上彌補了現(xiàn)有方法的一些不足之處。
  • In 1997 , the tax package in eu seeks to develop a co - ordinated approach to harmful tax competition and it plays an important role in internal market . recently , the eu has set itself the strategic goal " become the most competitive and dynamic knowledge - base economy in the world "
    其中， 1992年的魯丁報告、 1997年的稅收一攬子計劃和2001年的雙路線戰(zhàn)略是歐盟公司稅協(xié)調的三大轉折點，具有深遠的歷史意義，這三個部分是本部分也是本文的重點。
  • This research focused on applying the system analysis principle and mathematical modeling technique to study knowledge expression system for crop cultivation management . based on extensively collecting , understanding , analysis , and integration of expert ' s knowledge and experience , literature and experiment data for cotton cultivation management , the dynamic relationships of cotton growth and management indices to variety types , ecological environments and production levels were quantified , and a dynamic knowledge model for cotton management ( cottonknow ) was developed . by further incorporating the rule - based knowledge system for cotton management , a comprehensive and intelligent knowledge model - based decision support system for cotton management ( kmdsscm ) was established with component design
    本研究著重利用系統(tǒng)分析原理和數(shù)學建模技術來研究作物栽培管理的知識表達體系，在廣泛收集及充分理解和分析棉花栽培管理專家知識、經(jīng)驗和資料的基礎上，利用棉花栽培理論與技術方面的現(xiàn)有研究成果，并結合必要的試驗支持，解析、提煉和綜合棉花生育及管理指標與品種類型、生態(tài)環(huán)境及生產(chǎn)水平之間的定量化關系，首次構建了棉花栽培管理動態(tài)知識模型，并進一步結合基于知識規(guī)則的棉花栽培管理知識庫表達系統(tǒng)，設計和實現(xiàn)了綜合性、智能化和構件化的基于知識模型的棉花管理決策支持系統(tǒng)( kmdsscm ) 。
  • 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(jīng)網(wǎng)絡的泛化能力的因素,提出了一種新的結構自適應神經(jīng)網(wǎng)絡學習算法,在新方法中,采用了遺傳算法對神經(jīng)網(wǎng)絡的結構參數(shù)(隱層節(jié)點數(shù)、訓練精度、初始權值)進行優(yōu)化,大大提高了神經(jīng)網(wǎng)絡的泛化能力和知識動態(tài)獲取自適應能力;其次,構造集成神經(jīng)網(wǎng)絡,引入數(shù)據(jù)融合算法,實現(xiàn)了基于集成神經(jīng)網(wǎng)絡的融合診斷,有效地提高了知識獲取的全面性、完善性及精度;然后,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(shù)據(jù)補齊、連續(xù)數(shù)據(jù)的離散、沖突消除、冗余信息約簡、知識規(guī)則抽取等一系列的算法實現(xiàn)了智能診斷的知識規(guī)則獲取;最后,將粗糙集理論與神經(jīng)網(wǎng)絡相結合,研究了粗糙集-神經(jīng)網(wǎng)絡的知識獲取方法。
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