樣本集 的英文怎麼說

中文拼音 [yàngběnjí]
樣本集 英文
sample set
  • 樣 : Ⅰ名詞1. （形狀） appearance; shape 2. （樣品） sample; model; pattern Ⅱ量詞（表示事物的種類） kind; type
  • 本 : i 名詞1 （草木的莖或根）stem or root of plants 2 （事物的根源）foundation; origin; basis 3 （本錢...
  • 集 : gatherassemblecollect
  • 樣本 : sample book; specimen; advanced copy; sample; muster; scantling; instance; statistics
  1. The experimental results indicate that it is easy to be realized, can save the calculating cost and improve the constringency speed

    試驗結果表明，用粒子群演算法來訓練樣本集具有容易實現、節省計算成本和提高收斂速度等優點。
  2. In other words, we depend on the strong ability of classification of nn to recognize the characters of a car plate ; 4 ) under the precondition of inadequate samples, we introduce the technology of additional sample in the progress of characters recognition which uses experiential knowledge to construct some sample artificially and then inserted these samples into the sample set in order to improve the performance of network

    在字元的識別過程中，在使用較為簡單的圖像處理技術的基礎上，仍然使用構造性的覆蓋演算法，依靠神經網路強大的分類能力來對車牌字元進行識別： 4探討了在樣本數量較少的情況下，通過在字元識別過程中引入附加樣本的技術，利用先驗知識對原先的樣本集進行擴充，從而提高網路的性能。
  3. 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。
  4. Hi the aspect of symmetry analyzing to the hopfield model neural network with hebbian learning, we study on the dynamical behavior of the state space under the action of isometric transformation group g = z2 ? n, and prove the invariant property of the energy orientation ? / / " ) of the state space under the action of g. we find that the symmetry relationship of the network is sx - sw = sh when the active function of the neuron is odd, where sx is the symmetry of the patterns set x under hebbian learning rule, sh is the symmetry of the network and sw is the symmetry of the weight matrix w of the network

    ） s _ n為手段，研究了網路狀態空間在群g作用下各點的運動情況，證明了群g作用下的不變性。證明了當神經元的激活函數f為奇函數時， hebb法則下存儲樣本集x的對稱性s _ x 、網路對稱性s _ h以及連接矩陣對稱性s _ w三者之間滿足s _ x = s _ w = s _ h的關系；同時，我們還證明了：網路穩定態集vf同一s _ h軌道中的兩個穩定態的動力學行為（能量和吸引域大小）相同；兩個等距網路h和h 1 = g ? h ， （ ? ） g （
  5. In connection with the difference and distribution characteristic of the samples in sample space rs based on dga, a new self - adapted weight fuzzy omean clustering model of fault diagnosis of the power transformer based on the potential function is proposed. meanwhile, from the aspect of geometry characteristic of fc - divided in s dimension sample space, a method is proposed for the purpose of getting an effective adjacent radius, adaptive cluster number c and original cluster center of x sample set. for the diagnosis sample x, the property measure and diagnosis rule are proposed, which under the condition of potential density function that determine c number of optimal fuzzy cluster p1

    根據以變壓器dga數據為特徵量的樣本空間各樣本差異特性以及樣本在空間r ~ s的分佈特性，首次提出了基於勢函數自適應加權的變壓器絕緣故障診斷的模糊c -均值聚類模型；同時，從s維樣本空間的f ~ c -劃分幾何特性出發，提出了一種求取樣本集的類勢有效鄰域半徑和自適應求取聚類數和聚類中心初值的方法；對一個待診斷樣本，設計了基於類勢密度函數意義下的屬性測度和診斷準則。
  6. The model sample of tax2 in west sichuan is finally built up

    最終建立起川西孝泉?新場地區須二段的建模樣本集。
  7. We also prove the following properties : the stable states of the network in the same sh orbit have a same dynamical behavior, such as the size of attraction basin and the energy ; the relation of the symmetry of two isometric networks h and h ' = g - h is s ' h = g - sh - g ~ } for any isometry g, where sh and s ' h are the symmetry of h and h " respectively ; the isometry will not change the dynamical properties of the stable states set of the corresponding networks ; etc.

    ） g的對稱性s _ h和s _ n的關系為s _ h = g ? s _ h ? g ~ （ - 1 ） ；等距變換不會改變網路穩定態集的動力學性質等一系列的結論。所有這些研究結果表明了hebb學習法則是通過調整網路的連接矩陣，使得其的結構的對稱性包含存儲樣本集的對稱性這一存儲機理。
  8. We found that the ergodic method used to calculate the symmetries of a multidimensional system would give rise to the computing complexity problem, hi order to avoid the computing complexity problem, we present a novel approach using genetic algorithms for calculating the permutation symmetries of a patterns set and the weight matrix of the network. we design the corresponding computer program with visual c + + 6. 0 language. and numerical simulat

    並用wsualc語言分別設計了求解網路連接矩陣和給定樣本集的置換對稱性相應的遍歷法和遺傳演算法的程序，在pc機上進行數值模擬計算，比較遍歷法和遺傳演算法的計算結果。
  9. As for the undivided linear sample space, the kernel function is needed to map onto another high dimension linear space

    對于線性不可分的樣本空間，需要尋找核函數，將線性不可分的樣本集映射到另一個高維線性空間。
  10. Clustering analysis is one of most heated research topic of the day. data clustering, a unsupervised classifying method, is the process of grouping together similar multi - dimensional data vectors into a number of clusters or bins

    聚類就是把一個沒有類別標記的樣本集按某種準則劃分成若干類，使類內樣本的相似性盡可能大，而類間樣本相似性盡量小，是一種無監督的分類方法。
  11. On the basis of analyzing the method of producing traditional printer sample sets, an improved method to produce printer sample sets is presented, which enlarges the printer gamut availably and improve the color reproduction ability of the printer

    在分析傳統列印樣本集生成方法的基礎上，改進了印表機建模過程中列印樣本集的生成方法，該方法有效增大了列印色域，提高了印表機的色彩再現能力。
  12. This thesis takes up a corpus analysis based on the genre approach. it aims to work out the generic structure and the lexical - grammatical strategies employed by the counsel in the statements of defence and then to account for their choices of the moves and strategies

    作者在體裁分析的基礎上，運用樣本集合的分析方法，試圖分析得出律師在辯護詞中選用的體裁結構和語言策略，以及律師做出該選擇的原因。
  13. It also can use to reduce the computing freedoms of the weight matrix in associative memory designing by applying the symmetry relations of the network. regarding the artificial neural network as a dynamical system with symmetry will bring the corresponding geometric approach

    利用這種對稱性關系，既可以揭示「學習就是尋找樣本集對稱性」這一學習的內涵，又可以在聯想記憶網路的分析與設計中減小連接權計算的復雜度。
  14. Image targets swatch set is carve up to several subsets firstly, and each subset is corresponding to one output port of network. then a bp neural network can be constructed to complete vehicle target recognition. with the above method, image targets of several types of vehicles are tested in

    其基本思想是，先用改進的c -均值動態聚類方法將車輛目標的訓練樣本集劃分成若干子集，每個樣本子集對應神經網路的一個輸出埠，以此原則來構建一個bp神經網路，再代入樣本進行訓練后即可用於識別未知的車輛目標樣本。
  15. In this paper, we also put forward a incremental learning algorithm for such a model. when the number of new samples attains or exceeds the valve, we use these samples to make a model, and merge this model with current model, thus get a new current model

    針對這個問題，論文提出了一種增量學習方法:當新樣本集的樣本數達到或超過閥值時，用新樣本集建立一個模型，與當前的模型合併，得到最新模型。
  16. The quadratic optimization algorithms of support vector machine composed by chunking algorithm, fix - sample algorithm and sequential minimal optimization algorithm

    支持向量機二次優化演算法主要包括塊演算法、固定樣本集法和次序最小優化演算法。
  17. If there are plenty of samples, this system can diagnose pulverizing system fault exactly, and the system also includes explaining mechanism which can provide fault reason and fault dissolving method. it is obvious that the system can help to prevent pulverizing system fault happening and ensure the pulverizing system run safely and reliably

    在樣本集足夠豐富的情況下，本系統可對制粉系統所發生的故障作出較準確的診斷，再依據其解釋機制，對故障原因進行分析，並提出合理的解決措施，這對于制粉系統故障的預防和處理，提高運行人員的管理水平具有指導意義。
  18. The selection of classify attribute from web page training - set base on rough sets

    基於粗糙集的網頁訓練樣本集的分類屬性的選擇
  19. Through frequent testing on the temperature of the objects, the training sample assemblies are obtained

    通過對場景中物體的表觀溫度進行多次測量，得到訓練樣本集合。
  20. Another understanding about intrusion detection is viewing machine learning as a searching process, that is to say, intrusion detection is in essence the searching or approximation issue of intrusion rules in accordance to established searching strategy. after some concerned

    在基於遺傳學習的入侵檢測研究中，把機器學習看作一個搜索過程，即入侵檢測可視為基於訓練樣本集，按照既定的搜索策略對入侵規則的搜索或逼近問題。
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