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dynamic knowledge in Chinese

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

Translationmobile phoneMobile

  • 動(dòng)態(tài)知識(shí)

Examples

  • Evolutionary game of dynamic knowledge exchanging in knowledge interaction
    知識(shí)互動(dòng)中的知識(shí)交換行為進(jìn)化博弈分析
  • The effects of learner - generated diagrams on understanding and application of dynamic knowledge in explanatory text
    學(xué)習(xí)者生成圖解對(duì)說(shuō)明文閱讀理解和應(yīng)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(cè)試結(jié)果表明，本系統(tǒng)建立的知識(shí)庫(kù)結(jié)構(gòu)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(shí)空適應(yīng)性的棉花栽培管理動(dòng)態(tài)知識(shí)模型主要包括播前方案設(shè)計(jì)、生育指標(biāo)動(dòng)態(tài)和苗情診斷調(diào)控知識(shí)模型三個(gè)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(shí)態(tài)邏輯描述靜態(tài)知識(shí)的時(shí)態(tài)屬性以及動(dòng)態(tài)知識(shí)的時(shí)態(tài)關(guān)系和約束，把它們獨(dú)立出來(lái)作為時(shí)態(tài)知識(shí)進(jìn)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(yàn)告訴我們以大學(xué)為依托的經(jīng)濟(jì)實(shí)體對(duì)促進(jìn)愛(ài)爾蘭知識(shí)經(jīng)濟(jì)的蓬勃發(fā)展起著至關(guān)重要的作用，促使了未來(lái)更多、更好、更有價(jià)值的工作機(jī)會(huì)的持續(xù)性的增長(zhǎng)。
  • 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(jié)現(xiàn)在方法的基礎(chǔ)上，討論并實(shí)現(xiàn)了一個(gè)基于動(dòng)態(tài)知識(shí)庫(kù)的全文信息檢索系統(tǒng)( dkirs ) ，本系統(tǒng)試圖通過(guò)自動(dòng)構(gòu)建的動(dòng)態(tài)知識(shí)庫(kù)解決這兩類詞匯問(wèn)題，在一定程度上彌補(bǔ)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(bào)告、 1997年的稅收一攬子計(jì)劃和2001年的雙路線戰(zhàn)略是歐盟公司稅協(xié)調(diào)的三大轉(zhuǎn)折點(diǎn)，具有深遠(yuǎn)的歷史意義，這三個(gè)部分是本部分也是本文的重點(diǎn)。
  • 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(xué)建模技術(shù)來(lái)研究作物栽培管理的知識(shí)表達(dá)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(shí)、經(jīng)驗(yàn)和資料的基礎(chǔ)上，利用棉花栽培理論與技術(shù)方面的現(xiàn)有研究成果，并結(jié)合必要的試驗(yàn)支持，解析、提煉和綜合棉花生育及管理指標(biāo)與品種類型、生態(tài)環(huán)境及生產(chǎn)水平之間的定量化關(guān)系，首次構(gòu)建了棉花栽培管理動(dòng)態(tài)知識(shí)模型，并進(jìn)一步結(jié)合基于知識(shí)規(guī)則的棉花栽培管理知識(shí)庫(kù)表達(dá)系統(tǒng)，設(shè)計(jì)和實(shí)現(xiàn)了綜合性、智能化和構(gòu)件化的基于知識(shí)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(luò)的泛化能力的因素,提出了一種新的結(jié)構(gòu)自適應(yīng)神經(jīng)網(wǎng)絡(luò)學(xué)習(xí)算法,在新方法中,采用了遺傳算法對(duì)神經(jīng)網(wǎng)絡(luò)的結(jié)構(gòu)參數(shù)(隱層節(jié)點(diǎn)數(shù)、訓(xùn)練精度、初始權(quán)值)進(jìn)行優(yōu)化,大大提高了神經(jīng)網(wǎng)絡(luò)的泛化能力和知識(shí)動(dòng)態(tài)獲取自適應(yīng)能力;其次,構(gòu)造集成神經(jīng)網(wǎng)絡(luò),引入數(shù)據(jù)融合算法,實(shí)現(xiàn)了基于集成神經(jīng)網(wǎng)絡(luò)的融合診斷,有效地提高了知識(shí)獲取的全面性、完善性及精度;然后,針對(duì)知識(shí)獲取過(guò)程中所存在的不確定性、不完備性等問(wèn)題,探討了運(yùn)用粗糙集理論的知識(shí)獲取方法,通過(guò)缺損數(shù)據(jù)補(bǔ)齊、連續(xù)數(shù)據(jù)的離散、沖突消除、冗余信息約簡(jiǎn)、知識(shí)規(guī)則抽取等一系列的算法實(shí)現(xiàn)了智能診斷的知識(shí)規(guī)則獲取;最后,將粗糙集理論與神經(jīng)網(wǎng)絡(luò)相結(jié)合,研究了粗糙集-神經(jīng)網(wǎng)絡(luò)的知識(shí)獲取方法。
  • More examples：  1  2
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