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probability function中文是什么意思

  • 概率函數(shù)
  • 概率密度函數(shù)

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  • 例句與用法
  • Percolation probability functions for an infinite related model
    一類無窮相關(guān)滲流模型的滲流概率函數(shù)
  • In the next article in this series , i ll implement some probability functions using native php code , extend the
    在本系列文章的下一篇文章中,我將使用本機(jī)php代碼實(shí)現(xiàn)一些概率函數(shù),用幾個(gè)輸出方法擴(kuò)展
  • Probabilistic neural network ( pnn ) is a classification network , which is based on bayesian decision theory and probability function estimation theory
    D . f . specht提出的概率神經(jīng)網(wǎng)絡(luò)( probabilisticneuralnetwork , pnn )是基于密度函數(shù)估計(jì)和貝葉斯決策理論而建立的一種分類網(wǎng)絡(luò)
  • Because the basic probability function could not be gotten analytically , a fuzzy system replaces it and the fuzzy rules ' consequent parameters are gotten by the least squares method based on sampling data
    由于基本可信度函數(shù)不能解析獲得,用一個(gè)模糊系統(tǒng)對(duì)其予以等價(jià),模糊規(guī)則后件參數(shù)由樣本數(shù)據(jù)通過最小二乘法獲得。
  • Combined with the prior distribution of the model parameters and water quality observation data , joint posterior probability function which stands for the distribution characters was obtained by bayes ' theorem
    結(jié)合模型參數(shù)的先驗(yàn)分布和水質(zhì)監(jiān)測(cè)數(shù)據(jù),通過貝葉斯定理計(jì)算獲得了表征參數(shù)分布規(guī)律的聯(lián)合后驗(yàn)概率密度函數(shù)。
  • You shelled out to r to get these values , but i am worried that you will not have the time or inclination to install r . a native php implementation of some common probability functions would resolve that
    您需要交給r來處理以獲取這些值,但是我擔(dān)心您會(huì)沒時(shí)間或沒興趣安裝r 。某些常見概率函數(shù)的本機(jī)php實(shí)現(xiàn)可以解決這個(gè)問題。
  • Markov chain monte carlo simulation ( mcmc ) was taken to sample the posterior distribution to get the marginal posterior probability function of the parameters , and the statistical quantities such as the mathematic expectation were calculated
    通過馬爾科夫鏈蒙特卡羅模擬對(duì)后驗(yàn)分布進(jìn)行了采樣,獲得了參數(shù)的后驗(yàn)邊緣概率密度,并在此基礎(chǔ)上獲得了參數(shù)的數(shù)學(xué)期望等統(tǒng)計(jì)量。
  • It is hard to give the basic probability function in the process of using the evidence theory , so the model based on network and d - s evidence is put forward . the simulation of the example show it is feasible and effective
    針對(duì)運(yùn)用d - s證據(jù)理論時(shí)難以確定基本概率分配函數(shù)的問題,提出了神經(jīng)網(wǎng)絡(luò)與證據(jù)推理相結(jié)合的決策融合診斷方法,并通過實(shí)例驗(yàn)證了這種方法的可行性和有效性。
  • Based the basic principle of the accumulation of induced electric charges across the resistivity discontinuities and the induction current channeling inside the conductive bodies inspirited by the mt field , we set up the relation between the measured field on the earth surface and the distribution of the induced source underground by means of the defining the electric charge occurrence probability function and the electric dipole occurrence probability function and the spacial distributing of the " correlation probability " . the " image " of the field sources underground , or the distributing graphy of the induced electric charges and the induced current in the mesuring area can be drawed , from which we can get the outline of the geological anomaly on the meaning of the probability
    大地電磁場(chǎng)概率成像方法是一種新的地球物理成像反演方法,它是根據(jù)在大電磁波場(chǎng)的激勵(lì)下,地下介質(zhì)電阻率間斷處產(chǎn)生感應(yīng)電荷積累和導(dǎo)體內(nèi)部產(chǎn)生感應(yīng)電流,從而產(chǎn)生感應(yīng)電磁場(chǎng)的原理,相應(yīng)地定義了感應(yīng)電荷發(fā)生概率函數(shù)和感應(yīng)電偶極子發(fā)生概率函數(shù),通過“相關(guān)概率”發(fā)生的大小的空間分布,建立了地表觀測(cè)場(chǎng)與地下場(chǎng)源空間分布的內(nèi)在聯(lián)系。地下場(chǎng)源分布概率的“像” ,即測(cè)區(qū)的感應(yīng)電荷和感應(yīng)電流的概率的分布圖像,就是測(cè)區(qū)內(nèi)地質(zhì)體在概率意義下地質(zhì)異常體的分布輪廓。
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