概率取樣 的英文怎麼說

中文拼音 [gàilǜqǔyàng]
概率取樣 英文
probability sampling
  • 概 : Ⅰ名詞1 （大略） general outline 2 （神氣） manner of carrying and conducting oneself; deportment ...
  • 率 : 率名詞（比值） rate; ratio; proportion
  • 取 : Ⅰ動詞1 （拿到身邊） take; get; fetch 2 （得到; 招致） aim at; seek 3 （採取; 選取） adopt; assume...
  • 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
  • 概率 : [數學] probability; chance概率論 probability theory; theory of chances; 概率曲線 probability curv...
  1. Firstly the patterns of the multifingered hands are detailed, eight patterns are defined. the classical bayes method is used in the classification of pre - grasp of multiple fingers based on three patterns which are grasping, holding and pinching. based on the eight pre - grasp patterns, bp neural network is applied in the classification of the pre - grasp of multifingered hands and gets a good effect. the method solves the shortcoming input sample relying on the propobility density and simplified the un - insititution characters extraction. in this paper, support vector machine ( svm ) and binary - tree with clustering is applied in the classification. this method can solve the slow speed and effect with fewness sample in the classification, achieving a good effect. in this papper, we extract the characters of the regulation object with geometry characters and extact the unregulation object with the image analysis

    此法解決了輸入樣本依賴物體的概率密度的特點，簡化了分類特徵提取的不直觀性。本文還採用了支持向量機（ svm ）和聚類二叉樹相結合的方法對機器人手預抓取八類模式進行分類，解決了預抓取模式分類訓練速度過慢以及在分類中樣本數量偏少而影響分類效果的問題，得到了較高的正確率。本文對預抓取幾何形狀規則的物體採用直接提取其幾何特徵，對于預抓取幾何形狀不規則的物體採用圖像分析的方法進行特徵提取。
  2. For the cooperation of pile - soil, the complicacy of the structure system and the design and calculation system of the pile foundation, and furth er more for it ' s difficult to determine the properties of various kinds of soil due to the large scope of samples, there are still some problems in real applications. by the way it seems there is no document or report about the reliability analysis of pile bucking at present

    結構可靠度設計是近年來才提出的基於概率論的設計方法，由於樁土共同工作，樁基的結構體系和設計計算體系十分復雜，各種土性的取值因為樣本空間的非常龐大而難以準確確定，因此離實際應用尚存在一定問題，而對基樁屈曲的可靠度分析目前似尚未見文獻報道。
  3. A one - stage probability sample in which every member of the population has an equal chance of selection

    一種單一步驟概率抽樣法.人口中的每一個人都有同等的被抽取的機會
  4. A kind of probability sample in which a set interval is applied to a list often population to identity elements included in the sample ( e. g., picking every 10th name )

    一種概率抽樣.以一定的間隔來從人口名單中抽取所需的樣本（如:每隔10個人抽取一次）
  5. First, this paper gives an introduction of some methods of unequal probability sampling, their estimators and variance estimators, including sampling with pps with replacement, methods of sampling without replacement suggested by brewer, durbin, sampford, des raj, murthy, rao - hartley - cochran. then, at the basis of rao and bayless ' s study, we consider that population can be splited two random subpopulations, which are respectively drawn from different infinite super - populations, and compare the stabilities of estimators of the methods that given above. we find that the minor difference between two super - populations has great effect on the efficiency of the estimators for the population with moderately large coefficient of variation ( c. v. )

    本文首先從理論上介紹了若干種不等概率抽樣方法，它們的估計量、估計量的方差及其估計，其中包括有放回ppz及pps抽樣，不放回不等概率抽樣中的brewer 、 durbin 、 sampford 、 desraj ， murthy 、 rao - hartley - cochran等人的方法；其次，在rao和bayless兩人就樣本單元數n = 2的情形對上述抽樣方法進行比較的基礎上，將總體隨機地分成兩個子總體，視每個子總體取自不同的線性超總體，在文中，我們利用計算機實現隨機分組，並通過畫圖比較各方法估計量的穩定性，結果表明，對變異系數c . v . （ x ）較大的總體而言，兩個超總體之間的微小差異將對估計量的穩定性產生很大的影響，從而說明rao和bayless的比較結果還不夠完善。
  6. The thesis mainly recounts the detail questions about bayesian small sample theory and the important applications of the theory in engineering, and gives sufficient analyses and discussion of every step of accomplishing a precision evaluation when using small samples. in the thesis, the following issues are contained, such as how to get and denote the prior information, the consistence test of prior information and test samples of shooting range, the fusion of multi - source information, calculating of posterior probability, estimation with bayesian approach, how to constitute test evaluation project of different performance and calculate the risks of both sides are contained, and at last a kind of applied method to calculate the effectiveness is given

    論文主要敘述了有關bayes小樣本理論的一些具體問題，以及該技術在工程中的一些關鍵應用，對小樣本條件下精度鑒定的各個環節給予較充分的分析和討論，其中包括驗前信息的獲取、表示，驗前信息和靶場試驗樣本的一致性檢驗，多源信息的融合，驗后概率的計算， bayes方法在估計中的應用，試驗鑒定方案的制定，對不同戰標的評估方法和風險的計算等，最後對作戰效能的計算給出了一種工程中較實用的方法。
  7. Standard practice for probability sampling of materials

    材料的概率取樣的標準操作規程
  8. Practice for probability sampling of materials

    材料概率取樣慣例
  9. Practice for acceptance of evidence based on the results of probability sampling

    根據概率取樣結果進行數據驗收的慣例
  10. Standard practice for acceptance of evidence based on the results of probability sampling

    根據概率取樣結果所得數據驗收的標準實施規范
  11. Standard guide for using probability sampling methods in studies of indoor air quality in buildings

    建築物中室內空氣質量研究用概率取樣法的標準導則
  12. Thirdly, in order to improve the deficiency of these two algorithms, the paper presents an improved algorithm

    針對以上兩種方法的缺陷，本文提出了一種新的按概率取樣本的改進演算法。
  13. A choice has also to be made between probabilistic ~ techniques ( such as random or stratified ~ ) and non - probabilistic ~ techniques ( such as judgmental, quota or convenience ~ )

    另外要在兩種取樣方法中進行選擇，是選概率取樣法（例如隨機或分層取樣）還是選非概率取樣法（例如判斷取樣、定額取樣或方便取樣） 。
  14. Secondly, the paper shows the results from a great number of experiments of the weight algorithm that chooses samples by probability. the experiments point out that weight algorithm has a better generalization ability than the no weight algorithm. but a single weight algorithm is unstable and it needs tremendous time of calculation to combine many single algorithms into a stable one

    其次對按概率取樣本的有權值演算法進行了大量實驗，實驗結果顯示出按概率選擇樣本權值演算法比無權值演算法的總體性能更為優秀，但其個體演算法的不穩定性以及為了獲得穩定結果所需要的巨大計算時間使其不可能成為一種能廣泛應用的演算法。
  15. This paper presents a new face detection algorithm for color video images based on skin color and multimodal information fusion. first, this paper presents a new means for selecting skin samples ; and then comparing skin distribution in the eight color spaces and analyzing the adaptability for different skin patterns, poses a face initial orientation ' s method which uses the single gaussian model in the tsl color spaces, and calculates skin probability images ; afterwards comprehensive comparing three typical threshold value separating algorithms, put forwards a face separating method which bases on region growing and fuses multimodal informations ; final, raises a face confirming algorithm which fuses three shape features

    首先提出了?種新的膚色樣本選取方法；然後通過對八種色空間膚色分佈的比較以及不同膚色模型適應性的分析，提出了在tsl色空間上用單峰高斯模型模擬膚色分佈，求得膚色概率圖進行人臉初定位的方法；隨后在綜合比較三個典型閾值化分割演算法的基礎上，提出了融合多源信息進行區域生長分割人臉的演算法；最後提出了融合三個形狀特徵的人臉確認演算法。
  16. Idea : we cannot measure the closeness of the estimates with the population parameter directly, but it is possible to use data from a random sample to construct a set of values that contains the true value with a certain specified probability

    我們無法直接衡量估計值和總體參數之間的距離，但是利用來自隨機樣本的數據構造一個取值的集合，使得真值在給定概率下屬于這個集合是可能的。
  17. Recommended by china disabled persons ' federation, the survey is carried out through delamination, isometry, probability and multistage sampling, 734 nationwide counties ( cities, districts ) and 5980 subdistricts is taken out, almost 2. 6 million people, 2 of the national population, is referred

    中國殘聯介紹，這次殘疾人抽樣調查採用分層、等距、概率比例、多階段抽樣方法，從全國范圍內抽取了734個縣（市、區） 5980個調查小區，設計樣本量近260萬人，佔全國總人口的2 。
  18. Some new ideas are proposed in this thesis based on svm and ica : firstly, a modified svm method based on posteriori probability theory is given, which makes the classification super plane corrected from the original one. a better classification result is obtained without finding the best quadric optimization algorithm and large scale training datasets are reduced to small scale training datasets at the same time. secondly, ica is applied to the preprocessing period of the recognition character images for purpose of feature extraction and dimension reduction

    本文在系統研究svm和ica的基礎上提出了以下新的觀點：其一是採用了引入后驗概率的修正svm方法，它在原分類超平面的基礎上不斷修正分類超平面，提高分類正確率，從而避免了尋找最優二次規劃的麻煩，同時將大規模訓練樣本集化為小規模訓練樣本集；其二是應用獨立分量分析ica對需要進行識別的字元圖像預處理，提取字元特徵，降低輸入數據的維數，從而可以為下一步的svm識別過程提供好的數據集，用以提高識別率和識別速度。
  19. Therefore, it is the same with data mining with probability statistic character and knowledge discovery problems, especially with die problems that obtain sample information or need high cost

    因此，適用於具有概率統計特徵的數據採掘和知識發現問題，尤其是樣本難以獲取或代價過于昂貴的問題。
  20. We deeply discuss the importance of choosing sample sapce in two sides : one is the calculation of classical model of probability, the other is the independency of events, and the concept of probability should be fully used in the calculation of probability

    摘要從古典概型中事件概率的計算和事件的相互獨立性兩個方面，通過舉例較深入地分析了樣本空間選取的重要性，並指出在概率計算中要充分利用概率概念。
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