樣本值 的英文怎麼說
中文拼音 [yàngběnzhí]
樣本值
英文
sample value-
Categorical data in its broadest sense is simply a collection of values of discrete variable obtained from a sample of individuals of objects.
范疇數據在廣義上就是一批得自於個體或對像樣本的離散變量值。Employment of copula in the analysis involving bipit of extreme value samples
於二維樣本極值概率積分變換分佈分析中的應用Firstly, second harmonic component ratio and dead angles of two phase inrush ' s dispersion in three - phase transformes are acted as input variable. secondly, the method applies improved algorithm based on the original algorithm of multi - layer forward back propagation network, that is to say, adding last variational effect of weight value and bias value to this time and making use of variable learning rate. at the same time, this method also adopts dynamic form in the number of hidden floor node
首先，文中將三相變壓器兩相涌流差流的二次諧波含量比和間斷角作為網路的輸入變量；其次，利用對原有bp網路訓練演算法基礎上的改進型演算法（即在計算本次權值和閾值的變化時增加上一次權值和閾值變化的影響以及採用變學習率，與此同時隱含層神經元個數採用動態形式） ，通過樣本訓練使網路結構模型達到最優。Those inflexion are brought by the energy balance and heating mechanism in stellar chromosphere and corona. using large samples, we gain several credible numeric relation between different magnetic activity index and rotational parameters
我們通過對大樣本恆星的統計分析分別得到了晚型主序星磁活動與恆星自轉參量間以及磁活動與恆星色指數之間更廣泛意義的數值關系。Firstly, by numerical and theoretical analysis, the author compares some existent confidence intervals, for example, " exact " confidence interval, wald confidence interval and bayesian confidence interval, and finds some deficiencies points of the confidence intervals, whose modification version has been proposed. also, several better confidence intervals such as are also presented. secondly, for given confidence coefficient and interval width, the author constructs a class of asymptotical two - stage interval estimate procedures. at the same time, under varies restriction of confidence coefflcientent interval width, the optional sample size of the first stage has been computed by numerical computation. the numerical computation shows that the method considered in this dissertation have good properties and applied value
同時，由於poisson分佈的特性，我們知道不存在其參數區間長度小於0 . 5的置信區間，基於這些情況，我們主要展開了以下兩個方面的研究：一是利用數值計算分析與理論分析的方法對現有的若干置信區間如「精確」置信區間， wald置信區間， bayes置信區間等進行分析比較，發現了一些缺陷，針對這些缺陷，我們進行適當的修正，並得到幾種性質較好的置信區間如：修正大樣本區間jeffreys原則下置信區間二是針對已給定的置信系數與區間長度，我們提出了一種漸近的兩階段區間估計程序，並利用數值計算的方法，在各種置信系數與區間長度限定下，算出了最優的第一階段觀測次數（抽樣量） ，大量數據表明，本文考慮的方法性態良好，具有應用價值。According to the computer program, the preterit memory of the two pattern we designd exhibit explicitly, at the same time, the posterior distributing chart of those pattern dots have very important reference value
通過計算機程序實驗，我們設定的兩種模式下的歷史記憶情況清晰明了，並且該模式樣本點的后續走勢分布圖有很大的參考價值。We form a ly a line sample from spectra of 19 qsos in the literature. in this analysis, we demonstrate that a proximity effect is present in the data ; i. e., there exists a significant deficit of lines at zabs = zem, within 4h - 1 mpc of the qso emission redshift. and the deficit depends on the rest equivalent width of the lines, with weak lines showing a relatively weaker effect
我們發現所選樣本中確實存在接近效應，特別在z _ （ abs ） z _ （ em ）附近距類星體4h ~ （ - 1 ） mpc范圍內， ly森林的線數相對演化規律估計得到的線數缺少很顯著，並且與譜線的靜止等值寬度有關，弱線的接近效應較弱。This article puts forward a solution named divide - assemble by deducing the size of bp neural network to overcome entering the local best point, the dividing process is that a big bp neural network is divided into several small bp neural networks, every small bp neural network can study alone, after all small bp neural networks finish their study, we can assemble all these small bp neural networks into the quondam big bp neural networks ; on the basis of divide - assemble solution, this article discusses the preprocessing of input species and how to deduce the size of bp neural network further to make it easy to overcome entering the local best point ; for the study of every small bp neural network, this article adopts a solution named gdr - ga algorithm, which includes two algorithms. gdr ? a algorithm makes the merits of the two algorithms makeup each other to increase searching speed. finally, this article discusses the processing of atm band - width distribution dynamically
本文從bp網的結構出發，以減小bp神經網路的規模為手段來克服陷入局部極小點，提出了bp神經網路的拆分組裝方法，即將一個大的bp網有機地拆分為幾個小的子bp網，每個子網的權值單獨訓練，訓練好以後，再將每個子網的單元和權值有機地組裝成原先的bp網，從理論和實驗上證明了該方法在解決局部極小值這一問題時是有效的；在拆分組裝方法基礎上，本文詳細闡述了輸入樣本的預處理過程，更進一步地減小了bp網路的規模，使子網的學習更加容易了；對于子網的學習，本文採用了最速梯度? ?遺傳混合演算法（即gdr ? ? ga演算法） ，使gdr演算法和ga演算法的優點互為補充，提高了收斂速度；最後本文闡述了用以上方法進行atm帶寬動態分配的過程。The detailed works are as follows : the finding patterns problems in the time - series data sequence are described, and a new trend logic expression method is introduced, and its algorithm and experiment result of algorithm are given ; time - scries data are disposed, and using the arctg. slope of line as the sample of pattern recognition, so ignoring the aberrance of pattern in the classified. in addition, a new time - series pattern finding algorithm based on higher - order neural network is put forward
同時給出了本文的具體的工作，主要是：對在時序數據序列中發現模式問題進行了描述，並介紹了一種新的趨勢邏輯表示方法，給出了其演算法及演算法的實驗結果；對時序數據進行處理，提出了利用線段的斜率反正切值作為模式識別的樣本，從而在分類時忽略模式的畸變；另外，還提出了一個新的基於高階神經網路的時序模式發現演算法。A novel method based on artificial neural network bp algorithm to perform the parametric identification in deep foundation excavation is proposed hi the paper. taking in situs measurements as network input and parameters to be identified as network output, the network is trained with the samples obtained from fem computation
將某些現場實測值作為網路的輸入，土層物性參數作為網路的輸出，通過有限元正分析模型取得學習樣本來訓練網路，從而達到對深基坑開挖過程中的多層土體的物性參數進行辨識的目的。Defect style and imaging character of carbon product that easy create in the course of produce are analyzed, based on that, nineteen features are extracted form flaw stylebook
分析了炭素製品生產中易產生的缺陷類型及缺陷的成像特徵，在此基礎上，從缺陷樣本中提取了19個特徵值。The attenuation indexes of vertical direction components and level radial components of blast earthquake wave in the condition of far range are all larger than the one in the condition of close range. based on upwards analysises, relevant control ways and safety defending technology of blast vibration are given from the aspects of blast equipments, blast parameters, landform physiognomy, blast methods. and taking the practical data from blast scene as the sample, the blast shockproofness are forecasted by the feedforward nerve network model based on the prior knowledge of blast shockproofness, the regress analysis method and experience formula method, which supply the technology gist for
並且，以爆破現場的實測數據為樣本，採用基於爆破震動強度先驗知識的前饋網路神經模型、回歸分析法及經驗公式法分別對爆破震動強度進行了預測研究，為爆破施工參數的確定提供了技術依據，確保整個爆破工程順利安全進行，並對這三種方法的預測結果進行了對比分析;對比分析表明，三種預測方法計算出來的結果精度相差甚大，從檢驗樣本值與預測結果值之間的相對誤差可以看出，人工神經網路法預測的結果較其他方法更接近於實際值，回歸分析預測法的精度又要高於經驗公式預測法。A " brick - wall " low - pass filter can remove the images and leave the original spectrum, thus recovering the original signal from the samples
這種頻譜的重疊導致的失真稱為混疊，而重建出來的信號稱為原信號的混疊替身，因為這兩個信號有同樣的樣本值。However, via intensive numerical computation, the author finds that actually some characteristic of this confidence intervals, for example, confidence coefficient, expectation width and coverage efficiency fluctuate intensely when the sample size varies given the parameter, or when the parameter varies given the sample size
但是我們通過精細的數值計算發現，由於總體分佈的離散性，這些置信區間的特性（置信系數、期望長度、覆蓋效率）實際表現為當參數固定隨著觀測次數（樣本值）變化或當觀測次數固定隨著參數變化而發生強烈震動。Realization of improved bp algorithm - single output three layers " artificial neural network generator base on improved bp algorithm has been developed by the author, and the generator has some functions that the number of neuron in first and second layer and theirs related training parameters such as learning rate. momentum factor a and the value of sum error e can all be self - defined by the users ; connection weights and threshold in each layer ' s neuron training data and teaching signals can also be input or modified in the friendly interface
生成器功能是:網路結構中的第一、二層神經元個數和訓練參數中的學習速率粉，動量因子a和期望誤差值:可由用戶在一定范圍內自定義;各層的權值、閥值、網路初始樣本值及教師值可在友好的界面下輸入、修改。In this paper, we propose a scheme to solve the problem of outlier data patterns that the value of outlier data pattern is deleted first and then is predicted by the model of genetic algorithm and neural network
對于數據集中的異常樣本值，本文提出了一種解決方案：先刪除異常的屬性值，然後再用遺傳bp神經網路模型進行預測填補，通過實驗證明這種方案的可行性。From abnormal network flow view, first, we can define some statistical variables and use those variables to make a model, timely get data from network. then anids make full use of data in information lib to detect current network flow whether anomaly or not
若發現當前數據包異常，則進行報警。在異常網路流量檢測方面，首先確立測度集和建立模型，從網路中實時捕獲樣本值。其次，根據信息庫中保存的信息，對當前流量進行檢測。112 residual : the decoded difference between a prediction of a sample or data element and its decoded value
殘差：樣本值或數據成員的預測值與解碼值間的差值。The instantaneous probability density function of the virtual stochastic process is evaluated, and then the probability density function of the basic random variable is obtained by employing the independent random samples
利用獨立隨機抽樣的樣本值，即可獲取虛擬隨機過程的瞬時概率密度函數，進而獲得隨機變量的概率密度函數估計。By analyzing group of data, appropriate statistics, such as distribution and average of activity duration, distribution and average of project duration, etc were gained which can be used to determine a reasonable and executable schedule considering influence of random factors
運用這些模型在計算機上進行模擬試驗，得到一組工作時間參數的樣本值，通過對這組樣本值的統計分析，得到在隨機因素影響下工作持續時間的變化趨勢和平均值、項目工期的變化趨勢和平均值等參數值，從而為科學地進行進度管理提供依據。分享友人