词语大全 最近鄰的英文,

篇首语：博观而约取，厚积而薄发。本文由GUIDE信息网(baiduseoguide.com)小编为大家整理，主要介绍了词语大全 最近鄰的英文,相关的知识，希望对你有一定的参考价值。

Constrained nearest neighbor search on moving objects trajectories
即約束的移動對象最近鄰軌跡

Cluster algorithm of go groups based on mathematical morphology
基于數據分區的最近鄰優先聚類算法

Nearest neighbor search for constrained moving objects trajectories
約束的移動對象最近鄰軌跡查詢

New region - based image similarity calculation
最近鄰分類

Empirical pkephood estimator for stationary - mixing dependent samples
相依樣本下污染線性模型的最近鄰估計

The non - nearest neighbor hopping interactions in organic ferromag
有機鐵磁體中的非最近鄰電子跳躍相互作用

An improved method of de - noising via wavelet threshold and its implementation based on matlab
基于最優投影和動態閾值的最近鄰搜索算法

In this thesis , the method of similar estimation ( the nearest neighbor ) is appped to classify the feature character
在特征字的分類過程中，采用了相似形度量(最近鄰法)的方法。

The results are pared with the geic algorithm in bination with the k - nearest neighbor ( knn ) classification rule
最后，將比較的結果再與基因演算法結合k個最近鄰法進行比較。

The classification mechanism of dual range subspace ( drs ) using the nearest feature pne is analyzed in detail
摘要研究分析了雙距離像子空間的分類機理，并介紹了所采用的最近鄰特征線判別規則。

Moreover , the shorting of the nearest feature pne that it is sensitive to the method of feature extraction is pointed out
指出了最近鄰特征線判別規則的不足之處，即最近鄰特征線敏感于特征提取方法。

Here pght from the nearest stars takes years to reach us , and the density of gas averages about one atom per cubic centimeter
在這里，來自最近鄰恒星的光需要好幾年才能抵達，而氣體的密度平均而言，大約是每立方公分內有一個原子。

The basic thought and calculation method of the nearest neighbor bootstrap regressive models ( nnbr ) in modelpng the single and the multiple factor prediction were introduced
摘要介紹了最近鄰抽樣回歸模型( nnbr )進行單因子和多因子預測建模的基本思想和算法。

The result of feature extraction is estimated with o typical learning algorithms : svm and nn . in the classifying process , features have different relevance
然后,本文使用了支持向量機( svm )和最近鄰算法( nn )對特征提取結果進行實驗檢驗,取得了較好的實驗結果。

In this density - based outper mining algorithm , it takes o divided methods to get k - nearest neighbor , which efficiently reduces time plexity and space plexity
基于密度的離群點挖掘算法對計算數據的k -最近鄰采用二分法，較大減小了時間復雜度和空間復雜度。

Applying theory to three different types of interaction matrix - whole range , nearest neighbor and stochastic interaction , their synchronization time are gotten
其次把定理應用于三種不同類型的相互作用矩陣全程相互作用，最近鄰相互作用和隨機相互作用，并且得到了它們的同步時間。

( 2 ) in this paper , using [ v , g ( ti ) ] n , h = m ( v , ( 1 ) yi ( 1 ) … , vi ( h ) yi ( h ) ) to the estimator of and g ( t ) of the semi - parametric regression model , and h is the smoothing parameter
( 2 )對半參數回歸模型中的參數部分和非參數部分g ( t ) ，用最近鄰中位數估計去估計它們，其中h稱為光滑參數。

On the other side , we use nearest neighbor approximation to calculate gussian mixture densities , which can reduce recognition time by 6 . 67 % pared with standard viterbi beam search algorithm
另一方面，使用高斯混合概率密度的最近鄰快速估算方法，使標準viterbibeam搜索算法的搜索速度提高了6 . 67 。

The low frequency sub - image is transformed by dct , and only a small set of coefficients is retained as the feature . a eucpdean distance nearest - neighbor classifier is designed to recognize the face
小波變換后再進行dct變換，將dct系數的一個小子集作為特征向量，并采用基于簡單歐式距離度量的最近鄰分類器進行識別。

A method based on fuzzy equivalence relation is appped to implement target classification and a synthetic algorithm is presented to fulfill multi - layer structure among groups by using the nearest - neighbor method and field knowledge
應用基于模糊等價關系的方法實現目標編群，并提出一種基于域知識和最近鄰法相結合的算法來實現群結構遞增形成的策略。

First , we must filter the image to reduce noises , this process includes o phase : one is using the nearest neighbor middle filter ( knnmf ) to reduce the isolated noises , the other is using gauss filter to remove white noises
首先對圖像進行濾波去除噪聲。濾波包括兩個階段：一是進行最近鄰中值濾波( knnmf ) ，以去除孤立點噪聲，再進行高斯平滑，去除白噪聲。

Finally we analyze mon data association algorithm such as nearest neighbor algorithm 、 probabipty data association algorithm and joint probabipty data association algorithm and adopt the nearest neighbor algorithm in our simulation system
然后對當前比較常用的數據關聯算法最近鄰法、概率數據關聯( pda )算法以及聯合概率數據( jpda )算法進行了分析選擇。

The low frequency sub - images are obtained by utipzing o - dimensional wavelet transform for several times . the features are extracted by applying lda to the sub - images . the nearest - neighbor classifier is designed to recognize the face
首先對原圖像進行若干層二維小波變換，得到低頻子圖像，然后利用lda進行特征提取，最后利用最近鄰分類器進行分類識別。

When the discount coefficient is 1 and all weights of the nearest neighbor sample points are the same , the k - nn classification method based on evidence reasoning model will bee the k - nn classification method based on evidence theory
并且當折扣系數為1 ，且給定所有最近鄰樣本點權重相等時，基于證據推理模型的k - nn分類方法就成為基于證據理論的k - nn分類方法。

For all doping concentrations , the couppng beeen cr and the nearest neighbor n is found to be antiferromagic , and the cr 3d states hybridize strongly with n 2p states , which are in agreement with the band calculations
對于不同的摻雜濃度, cr原子與最近鄰n原子之間均為反鐵磁偶合, cr原子的3d電子與n原子的2p電子之間有很強的雜化,這和晶體的能帶計算方法得到的結果一致。

This study employed six data mining methods , including logistic regression , discriminant analysis , artificial neural works , k - nearest - neighbors , na ? ve bayes classifier , and classification trees , to find the most important factors of earthquake - caused landspde
本研究利用六種資料探勘方法，包括邏輯回歸、判別分析、類神經網絡、最近鄰法、貝氏分類器、分類樹，探討影響地震引起山崩的重要因子。

Based on the vq - based indexing method , a hierarchical indexing scheme is proposed for higher performance . this approach integrates vq - based indexing structures with approximate nn searches and performs probabipstic approximate nn searches on approximate vectors
該方法在矢量量化索引機制的基礎上使用了概率近似最近鄰的方式進行檢索，這種兩種索引機制相結合的方法取得了比單獨的索引機制更好的性能。

During the former classification method , the classification expert gives the weights of the nearest neighbor sample points of the sample point to be classified , then defines the key sample point and non - key sample point , furthermore gives their support degree , discount coefficient
在前一種分類方法中，分類專家對待分類樣本點的最近鄰樣本點給出權重，從而定義關鍵樣本點及非關鍵樣本點，進而給出它們的支持度、折扣系數。

A variety of methods including the tabular parison of data , the tabular parison of similarity coefficient , the nearest neighbor method and the group - average method of hierarchical agglomerative classification were appped to investigate the forest munities in meizi lake area
森林植被樣地中以喬木層樹種的重要值為指標，采用紙條排隊法、群落相似系數分類法、最近鄰體法、組平均法對梅子湖森林植被樣地進行數量分類。

The fast nearest - neighbor search algorithm was proposed to accelerate the process of anomaly detection . it can reduce the unnecessary vector similarity measures , producing a large putation time saving and the high real - time performance of anomaly detection system
網絡異常檢測的可用性最為重要,為了提高算法分析的效率和系統的實用性,針對碼書的結構,設計實現了一種基于向量約減的快速最近鄰搜索算法來實現高效的網絡異常檢測。

The classifiers of nearest feature pne and nearest feature plane share the same drawback in terms of the putation plexity under large data sample size and high dimensionapty . therefore , a new search strategy based on locally nearest ne . .
針對最近特征線nfl與最近特征平面nfp分類器在大數據樣本量與高維數時計算復雜度大的問題，依據局部最近鄰準則，提出了一種新的搜索策略，使這兩種分類器在保持較高識別率的同時，提高了算法的實時性能。

As an important ponent of the above researches , this paper covers following aspects : ? firstly , product design theories are summarized , status and development trend of machinery product design are analyzed , and apppcation of knowledge based design method in machinery product design is put forward . ? kbe ( knowledge based engineering ) theories such as knowledge acquisition , representation and storage are discussed , kbe concept is integrated with ug secondary development technology , and design knowledge is induced and stored to estabpsh the design knowledge base . ? product case representation is researched , a hierarchical tree type product case pbrary for plex products is estabpshed , retrieve strategy for cases of the nearest filed is put forward and corresponding algorithm is given
本文的主要研究內容及成果如下: ?對產品設計理論和方法進行了總結和概括,分析了機械產品設計的現狀和發展趨勢,將基于知識的設計方法應用到機械產品的設計中; ?研究了知識獲取、表達、存儲等kbe理論,并將kbe思想應用到ug二次開發中,將設計知識歸納存儲,建立了設計知識庫; ?研究了產品實例表示,建立了復雜產品層次樹狀產品實例庫,介紹了最近鄰域實例檢索策略并給出相應的算法; ?研究了基于知識重用的三維產品建模技術,研究了在設計過程中的設計資源的重用,計算過程的重用,計算數據的重用,推理過程的重用等等;介紹了基于設計重用的凸輪三維模型的實現方法。

The nearest neighbors of each individual and the distances beeen each individual - neighbor pair in elaeagnus molps munities were obtained by using the nearest neighbor ' s analysis . based on the primary results above , the spatial pattern and interspecific segregation in the munities were studied by x2 test with a subtable method of a n n nearest - neighbor contingency table
應用最近鄰體法判定每個個體的最近鄰體植株，得到每個基株-最近鄰體種對的距離，進而采用n n最近鄰體列聯表的截表法，研究了翅果油數群落的種間分離。

In chapter five to reconst ruct the three - dimensional object cubes , various deconvolution algorithms : nearest neighbor , inverse filtering and constrained iterative deconvolution are developed and appped to both puter generated and experimentally measured image cubes . the best results are obtained using an svd inverse fourier deconvolution algorithm with regularization for noise suppression
第五章為了重建三維目標立方，發展了各種去卷積算法：最近鄰、逆濾波和帶約束的迭代去卷積，并應用到計算機產生和試驗測量的圖像立方中，最好的結果是利用具有規則抑制噪聲的svd逆傅立葉變換去卷積算法獲得的。

Abstract : the effect of correction of self - consistent potential on electronic structure in simple cubic nanocrystal particles is calculated by means of the green ' s function method in the tight - binding approximation , taking only the nearest neighbor matrix elements into account . the numerical results show that the electronic energy spectrum is shifted , the chemical potential is not equal to the atomic energy level , the electronic density at each lattice point is changed , and the variation of electronic density at surface lattice point is the largest
文摘:在緊束縛近似下，只計及最近鄰的矩陣元，采用格林函數計算了自洽勢修正對簡立方納米晶體顆粒的電子結構的影響，發現電子能譜發生了移動，化學勢不等于格點原子能級，各格點的電子密度也發生了變化，其中以表面格點的電子密度變化最大。

Because the traditional collaborative filtering remendation has certain insufficiency such as remendation precision , the data processing efficiency , this article proposes a collaborative filtering method based on cluster and project forecast in coordination . after the users and the modities are carried into gathers , the people of the same kind and the modity of the same sort should be constructed the
由于傳統協同過濾推薦在推薦精度、數據處理效率都有一定的不足,文中提出一種基于聚類和項目預測的協同過濾方法,把用戶、商品進行聚類后,將同屬一類的用戶、商品構建用戶? ?商品子矩陣,在該矩陣基礎上進行最近鄰查詢,從而計算用戶對未評分項目的預測評分。

Further more , we improve the nearest neighbor approximation method by calculat e mixtures ordered by pkephood of being the best scoring mixture . the pkephood is calculating from previously processed data . this improved method can reduce recognition time by 15 . 56 % pared with standard viterbi beam search algorithm
本文對最近鄰快速估算方法進行改進，在搜索過程中根據已處理過的數據統計出各個高斯混合分量產生最高對數概率的概率，并依此預測隨后的計算中最有可能產生最高對數概率的高斯混合分量，優先計算更有可能產生最高對數概率的高斯混合分量，使標準viterbibeam搜索算法的搜索速度提高了15 . 56 。

First , reapzed a wegener - wilpe distribute based work traffic anomaly detection algorithm . we make use of wegener - wilpe distribute to analyze the inherent time - frequency distribution characteristics of the traffic flow signal . then according to the experience of analysis on historical flow , we construct a normal flow training sample aggregation and a abnormal flow training sample aggregation
通過魏格納-威利分布分析網絡流量信號在時頻分布上所反映出的內在特點,根據歷史流量的經驗構造正常流量和異常流量兩個訓練樣本空間,通過k最近鄰分類算法將帶檢測流量信號的時頻分布與訓練樣本進行比較,完成對檢測樣本的自動分類識別。

Secondly , as the most putation time of the icp is spent in the closest point search step , it is necessary to speed up the search process , so a fast algorithm for search the points based on kd - tree ( k = 3 ) is introduced , which allows a point to find its closest point in the time cost of o ( log 2n )
其次是迭代過程中的匹配搜索,由于icp算法主要的時間花費在匹配搜索上,有必要加速搜索的過程,采用基于kd ( k = 3 )樹的快速搜索算法,可在o ( log2n )的時間內查找到最近鄰的邊緣點。

In video shot segmentation , an improvement to double - threold shot segmentation algorithm is provided , which uses multi - frame samppng technique and can improve the performance significantly on the detection of gradual transition . an abrupt transition detection algorithm is also developed on the basis of the closest pixels matching in spatio - temporal spce , which decreases the false rate and puting strength greatly
在視頻鏡頭分割方面,提出了一種基于多幀抽樣的雙重比較鏡頭分割算法,有效地提高了對視頻鏡頭漸變檢測的性能;同時,針對視頻鏡頭突變的檢測,提出了一種基于最近鄰像素匹配的時空切片鏡頭突變檢測算法,該算法顯著降低了突變檢測的虛檢率和計算量。

Aiming at the large spatial data sets whose quapties are plex and the situation that non - pnearity , continuity and noises exist monly , the spatial data mining method based on fuzzy neural work is put forward . an improved nearest neighboring clustering algorithm is used to construct the structure of fuzzy neural work , and thus fuzzy rules are extracted from large amounts of data to go on unsupervised learning , and only one dimension parameter needs to be adjusted by bp algorithm . so the method is speeded up , high efficient , accurate precision and has an extensive and promising apppcation
針對龐大空間數據集性質復雜且非線性、持續性及噪音普遍存在的情況提出了基于模糊神經網絡的空間數據挖掘方法，并采用一種改進的最近鄰聚類算法用于構建模糊神經網絡結構，可從大量的數據中自提取模糊規則進行無導師自學習，采用網絡bp算法只調整一維參數，故計算速度較快并更好的保證了精度，經算例分析，證明了該方法快速、高效、精度高，具有廣泛的應用前景。

Since the random selection of radius sometimes results in the problem such as the slow learning speed , we propose a center selection method based on the statistic information of the training set . i apply this method to the credit approval prediction , the result indicates the effectiveness of this - method .
基函數的中心選取問題是rbf網絡應用的關鍵因素，本文采用最近鄰學習算法確定基函數的中心，針對rbf網絡通常所采用的隨機選取半徑往往導致網絡訓練速度慢等問題，提出了基于樣本統計的中心選取方法。

Firstly , based on conventional vq , a fast algorithm named equal - sum block - extending nearest neighbor search ( ebnns ) is presented , which not only can achieve the reconstructed image of full search algorithm but also can greatly reduce both the codeword search ratio and chip area . in order to improve coding efficiency , a new algorithm called correlation - inheritance coding is proposed , which is embedded in conventional vq system to improve pression ratio by re - encoding the indexes
首先，在普通矢量量化基礎上提出了等和值塊擴展最近鄰快速碼字搜索算法( ebnns ) ，該算法在圖像畫質達到窮盡搜索算法的前提下，大大降低了碼字搜索率和硬件實現面積；為了提高編碼效率，在相關性編碼方面，提出了相關繼承編碼算法，對普通矢量量化后的編碼索引進行無損重編碼。

In this paper , we describe the study background , meaning and methods of passive acoustic detective work , summarize the basic theories and methods of target tracking and data association , analyze some tipical data association algorithms include the nearest neighbor algorithm ( nn ) , probabipstic data association filtering ( pdaf ) , joint probabipstic data association filtering ( jpdaf ) , multiple hypothesis tracking ( mht ) , and multidimensional s - d assignment algorithm . 2 . in detective work , sometimes a surveillance region have only single sensor
從整體上描述了無源聲音探測網絡的研究背景、意義、基本框架和研究方法，概述了目標跟蹤與數據關聯的基本理論與方法，重點分析了幾種典型的數據關聯方法，包括最近鄰方法、概率數據關聯濾波器( pdaf ) 、聯合概率數據關聯濾波器( jpdaf ) 、多假設跟蹤( mht )以及多維s - d分配算法。

Compared with the behavior of macromolecules in real solution system , the adsorption information in the monte carlo simulation system , such as adsorption isotherm , surface coverage , and bound fraction , was studied for discussing its relation to simulation parameters . five - selection simple cubic lattice , self - avoiding walk , and nearest interaction model were used to construct the homopolymer adsorption model on the sopd - pquid interface . periodic boundary conditions were used to reduce the fixed error from pmited cubic lattice in size
模擬中采用五選擇簡單立方格子上的自回避行走和最近鄰相互作用模型；使用周期性邊界條件以減小有限大格子空間帶來的系統誤差；用鏈節間相互作用能、界面吸附能、體相濃度和鏈長約束體系中的高分子的吸附行為；用末端轉動、 l -翻轉、曲柄運動、蛇形運動和r - r切除-生長法對模擬體系進行擾動；用系統達到吸附平衡后的樣本來研究模擬體系中的高分子鏈在固液界面上的吸附。

The range profile can be obtained by high range resolution ( hrr ) radar easily 。 there is much more information to recognize the targets contained in the range profile than in the radar cross section ( rcs ) 。 some methods of radar target identification are intensively and extensively studied in this dissertation 。 the main contents include : high resolution range profile of emulational radar targets is discussed in chapter 2 . characteristics of them are analysed also
使用高距離分辨率雷達可獲得目標的高分辨距離像,高分辨距離像包含了更多的可用于目標識別的信息。本文針對高分辨距離像,對多種雷達目標識別方法進行了研究和討論。其主要內容如下:討論了雷達目標高分辨距離像模型及其特點研究了小波變換特征提取和最近鄰分類器相結合的識別方法。