隱含利息 的英文怎麼說
中文拼音 [yǐnhánlìxī]
隱含利息
英文
implicit interest-
However geological information is fully recorded in the remote sensing image, which made it possible for the choosing of this area as a dissection point to extract complex structural information of orogenic belt in west china. taking fully advantage of multi - band image richly bearing concealed geological information in combination with remote sensing analysis and structure analysis, to anatomy the supracrustal composition and structure of orogenic belt with the regional linear structures and their partitioned block and schistous geological masses as the macro - frame ( in corresponding to structure units and structure segments ) and with the rock masses, structure - rock assemblages, line - featured and belt - featured structures as well as penetrative and non - penetrative foliation ( primary stratum and trans position layering ) and folds as the texture and structure elements. the methods of how to distinguish granulite > ductile - shear zone, imposed fold, different deformed belts -
因而，本文選擇這一地區作為我國西部地區從遙感圖像上提取造山帶復雜結構構造信息的解剖區，充分利用遙感圖像多波段反映物質屬性的特點和圖像處理提取隱含信息的優勢，採用遙感解析?構造解析相結合的研究方法，以區域線狀構造及由它劃分的塊狀、片狀地質體為宏觀骨架（對應于構造解析劃分的構造單元、構造均勻區段） ，以地質體中的巖石巖體、構造巖石組合，線狀、帶狀構造，透入性、非透入性面狀（原始層理、新生面理）和褶皺等構造作為用於解析的結構構造要素，進行造山帶表殼組成和結構構造解析研究。In this text, we first do some research on the genetic algorithm about clustering, discuss about the way of coding and the construction of fitness function, analyze the influence that different genetic manipulation do to the effect of cluster algorithm. then analyze and research on the way that select the initial value in the k - means algorithm, we propose a mix clustering algorithm to improve the k - means algorithm by using genetic algorithm. first we use k - learning genetic algorithm to identify the number of the clusters, then use the clustering result of the genetic clustering algorithm as the initial cluster center of k - means clustering. these two steps are finished based on small database which equably sampling from the whole database, now we have known the number of the clusters and initial cluster center, finally we use k - means algorithm to finish the clustering on the whole database. because genetic algorithm search for the best solution by simulating the process of evolution, the most distinct trait of the algorithm is connotative parallelism and the ability to take advantage of the global information, so the algorithm take on strong steadiness, avoid getting into the local
本文首先對聚類分析的遺傳演算法進行了研究，討論了聚類問題的編碼方式和適應度函數的構造方案與計算方法，分析了不同遺傳操作對聚類演算法的性能和聚類效果的影響意義。然後對k - means演算法中初值的選取方法進行了分析和研究，提出了一種基於遺傳演算法的k - means聚類改進（混合聚類演算法） ，在基於均勻采樣的小樣本集上用k值學習遺傳演算法確定聚類數k ，用遺傳聚類演算法的聚類結果作為k - means聚類的初始聚類中心，最後在已知初始聚類數和初始聚類中心的情況下用k - means演算法對完整數據集進行聚類。由於遺傳演算法是一種通過模擬自然進化過程搜索最優解的方法，其顯著特點是隱含并行性和對全局信息的有效利用的能力，所以新的改進演算法具有較強的穩健性，可避免陷入局部最優，大大提高聚類效果。By taking advantages of epipolar line features and depth discontinuities in reference 中國科學院 軟件 研究所 博士 學位 論文 基于 圖 象 的 快速 繪制 技術 的 研究 images ， an efficient inverse wmping algorithm is pfoposed in chapter 3 for gcnerating nagcs of novel views by combining multiple eference images 帆 enhm different vie 呷 oints because continuous segnents determi 。 d by pairs ofedge pixels at co 。 spending epipolar lines are order kept ， only pairs of edge pixels in the reference 渝 明 e e necess 叨 口 cowute to obtain generalized disparity of all points in the desired image as a result ， sighficant acceleraion could be made in the endering pfo 比 鴕 two accelerating techiq 此 s e presented in this algori 山 mb accelerate the hole illing process his algorithm extends the reference images rom projection of single col ： ii ’ ected surface in previously developed nvnverse w 出 下 er to ima 驢 s captured rom complex scene in chapter 4 ， an 《 dent ibr method is prese 庇 仙 y takn ull 訕 antage of 呷 bies c 咖 the method can simulate the 3d details on sllri ： ace of object successfully he 。 叩 proach ， called rered ature mopmp consists of two pans at fst ， an origi 。 ltexture with orthogonal displacements per pixel is deco 啊 osed into a series of new t6 刀 mfcs with each 他 lug a given displacement per pixel ， called ae ， ea atures ， or lt hen hese lt e used to render the novel view by conventional texture mapping d avoid gaps n the endered hlla 驢 ， some phels are to be interpolated nd extended in the 廠 kaccoding to the depth differe eee between two neighbor pixels in the original texture as these ltlt fc … e much storage nd therefore much time is equired to install ltlt into the text ’ ufc buffec an 舊 thod is pfoposed to co 呷 fcss the ltlt ， nd the cottcspondingfclldering method is given experimental esults show that the new method is efficient ， especially n rendering those objects with a smaller depth rnge compared withtheir size ， such as relief surfaces of building
與己有的三維變換方法相比較，該方法不但成功地填補了由於投影區域擴張而產生的第一類空洞，而且成功地填補了由於空間深度非連續物體相互遮擋而產生的第二類空洞，從而方便地實現了虛擬環境中的漫遊；基於物體表面深度的連續性，本文提出了一個位移預測方法? ?此方法可以從單幅參考圖象獲得逆映射過程中所需要的目標圖象的位移信息，從而大大提高了演算法的效率：與通常的正向映射演算法相比，此演算法克服了多幅參考圖象所帶來的計算量成倍增長等問題，而且誤差較小。 2 ）基於極線幾何的快速逆映射演算法。利用參考圖象的邊界信息與隱含的遮擋關系，以及極線幾何的性質，本文第三章提出了一個基於極線幾何的快速3 『一中國科學院軟體研究所博士學位論文基於圖象的快速繪制技術的研究逆映射演算法，從多幅參考圖象精確合成當前視點目標圖象。Because these datu are too large and discrete, it is a difficult and complex task to analysis categorize, index and look up them with traditional artificial methods. and it is more difficult to research into the implicit laws which hide in quality control and management. so, to explore the enterprise ' s information resources efficiently is impossible, and the quality of production can not be pledged well, not to mention make decision - making scientifically
眾所周知，在水泥生產製造過程中，會產生大量的質量數據，但由於這些數據類繁、量大且分散，以至傳統的人工處理方式對其進行分析、歸類、檢索和查找成為一項艱巨復雜的工作，更難于揭示歷史數據中所隱含的質量控制和管理規律，從而難以對企業質量信息資源進行充分開發利用，致使企業產品質量難以提高，嚴重地影響質量決策的科學性。Web data mining has been combined with electronic commerce on this occasion. it is a new branch of data mining and focuses on the research in the internet on how to find out all implicit knowledge modes among all kinds of data including web logs, user register information, web page etc, and on how to gain some predictive information
Web數據挖掘就在這樣的背景下與電子商務結合在一起，它是在internet出現后產生的數據挖掘一個新的分支，主要研究在internet網路上，對各種數據源，如web日誌、用戶登記信息、頁面內容等，利用數據挖掘技術尋找網路上數據間各種隱含的知識模式和獲取一些預測性信息。The second of these solutions might be more manageable within the context of china s existing corporate law, to be implemented by issuing a special class of the management company s securities to shareholders of the funds under management and defining the role of independent directors in the portion of the management company s charter or constitution that creates that class of securities
法瑪1970還進一步細分了三種有效市場，從而說明價格反映所有的公開信息，基本分析者的共識形成公平價格。所以emh已經隱含了已知信息不能用來在市場上獲利的命題。我們也可以說，到了法瑪那裡， emh依賴于理性投資者。Ga is a computational models of the human evolution, with implicit parallelism and capacity of using effectively global information
遺傳演算法（ ga ）是一種通過模擬自然進化過程搜索最優解的方法，其顯著特點是隱含并行性和對全局信息的有效利用能力。The paper introduces some common methods used in data - mining ’ s calculating, process and data pretreatment. it digs out the implied connection among criminals ’ data information after analyzing and dealing with all kinds of criminals ’ data information in a certain prison ’ s database. and though the study on decision tree c4. 5 algorithm, we utilize the algorithm set up a model of criminal shortening the term of imprisonment, and give some classify of factor of criminal shortening the term of imprisonment
本文介紹了數據挖掘常用的演算法，數據挖掘的步驟以及數據預處理技術，針對某一監獄管理局的罪犯信息數據庫，對罪犯數據間的各種信息進行分析處理，挖掘出了罪犯數據信息間的一些隱含關系，以及通過對決策樹c4 . 5演算法的研究，利用該演算法建立了罪犯減刑效果模型，用來對影響罪犯減刑效果的因素進行分類。With the increasingly keen industry competition caused by the globalization of economy, enterprises in information age are compelled to capture opportunities and build up their core competition ability by utilizing knowledge concealed in large amount of data
經濟的全球化導致行業的市場競爭日益激烈，信息時代的企業必須利用大量數據中隱含的知識才能抓住時機，提升核心競爭力。This paper studies 3 kinds of algorithms : the viterbi algorithm, multiresolutional algorithm based on wavelet transformation and bayesian bootstrap algorithm. the viterbi algorithm is based on the hidden markov model theory and it is a kind of map estimation, this paper studies this algorithm and puts up an algorithm that suits for filtering in the presence of interference. multiresolutional algorithm takes full advantage of multiresolutional data, we can see it has a better filtering ability than the traditional filtering methods ; bootstrap algorithm is a recursive bayesian estimation, it describes the probability density function by the samples, so it can be used to nonlinear non - gaussion filtering, the simulation result of the two groundings is presented
Viterbi演算法以隱馬爾可夫理論為基礎，是一種最大后驗概率估計方法，本文對該演算法進行了研究，給出了一種適合於非高斯干擾條件下的濾波方法；多分辨分析方法充分利用到了多解析度測量數據所包含的信息，從模擬結果中可以看出，該方法的濾波精度要高於傳統的濾波演算法；自主濾波方法是一種遞推貝葉斯估計演算法，它利用采樣點來描述目標狀態的概率密度函數，因而適用於非線性、非高斯條件下的濾波，本文分別對這兩種情況下的濾波進行了模擬。Data mining, also named as kdd ( knowledge discovery in database ), is a decision support method in which we can pick up many connotative, unkn - own, potential and useful knowledge or information mode from database or data warehouse. the knowledge that is discovered by means of data minning can reflect a certain facts and guide practice
數據挖掘（ datamining ） ，又稱知識發現，是利用各種分析工具在存放海量數據的數據庫或數據倉庫中提取隱含的、先前未知的、潛在有用的知識或信息模式的決策支持方法。通過數據挖掘發現的知識能夠反映一定的客觀事實，並指導實踐。The result shows that the information indicating the changes of the running state included in data monitoring can be extracted in the time domain and frequency domain by wavelet transformation
研究結果表明，利用小波變換能同時在時域和頻域上提取出監測信號所隱含的表徵系統運行狀態變化的信息。But by far neither well - grounded explanations nor rationalization proposals were put forward. whereas as early as the beginning of last century, western scholars had noticed the phenomenon in credit market that borrowers couldn ’ t get loans at current interest rate even though they were willing to pay the rate. this phenomenon was defined as “ credit rationing ”, and was gotten explanations from aspects of availability of credit, factors of risks and interest rate, implicit credit contract, imperfect information, implementation of credit contract and legal system
另一方面，早在上個世紀初，西方學者就注意到了信貸市場中這種借款人願意支付現行利率，卻不能按照這種利率獲得貸款的現象，將其定義為「信貸配給」 （ creditrationing ） ，並從信用可獲性、風險與利率因素、隱含性信貸合約、不完全信息、信貸合同的執行和法律制度等角度進行了解釋，但這些主要以完善市場經濟為研究對象的理論僅一定程度上適合中國農村，轉型時期的中國農村信貸配給現象還需要結合其特殊的經濟、金融情況進行解釋。By using quantitative analysis of oral code and qualitative analysis of oral material, we conclude that the top students do much better than secondary students on digging out latent information, distinguishing the mode, and choosing object in unitary aspect, however, the difference in reasoning between the two is not so distinctive as that in past research
我們認為，優等生較之中等生更加善於挖掘隱含信息、進行模式識別、利用整體法考慮問題，而兩者在一般推理方式上的差異則不象以往研究那樣顯著，並且，優等生較之中等生更加善於自我調控。分享友人