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regression prediction中文什么意思

發(fā)音:   用"regression prediction"造句
  • 回歸預(yù)測
  • regression:    n. 1.復(fù)歸，回歸。 2.退步，退化。 3.【天文學(xué)】 ...
  • prediction:    n. 1.預(yù)言，預(yù)告。 2.被預(yù)言的事物。 3.【氣象學(xué) ...
  • regression:    n. 1.復(fù)歸，回歸。 2.退步，退化。 3.【天文學(xué)】退行。 adj. -sive ,-sively adv.
  • prediction:    n. 1.預(yù)言，預(yù)告。 2.被預(yù)言的事物。 3.【氣象學(xué)】預(yù)測，預(yù)報。 weather prediction 天氣預(yù)報。
  • adaptive regression:    適應(yīng)退化; 適應(yīng)消退
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例句與用法

  1. The bilinear regression prediction model was established for estimating the composition of the mixtures , and method is simply and reliably and with good results
    應(yīng)用兩元回歸模型可預(yù)測三元混合物的組成，方法簡便、測量準(zhǔn)確、可靠，相對誤差小于5 % 。
  2. Accordingly , the thesis proposes four models for predicting the remaining life of concrete bridges , which are regression prediction model , grey prediction model , improved grey model and neural network model
    為此，論文給出了橋梁結(jié)構(gòu)剩余壽命預(yù)測的四種模型，即回歸預(yù)測模型、灰色預(yù)測模型、改進灰色模型和神經(jīng)網(wǎng)絡(luò)預(yù)測模型。
  3. ( 4 ) the applications of bp neural network prediction gm ( 1 , 1 ) prediction of new information with the same dimension non - linear exponential regression prediction in regional social - economic indexes are discussed in this paper
    ( 4 )探討了bp神經(jīng)網(wǎng)絡(luò)預(yù)測、灰色gm ( 1 ， 1 )等維新息模型預(yù)測和非線性指數(shù)回歸預(yù)測等方法在區(qū)域社會經(jīng)濟指標(biāo)預(yù)測中的應(yīng)用。
  4. For the information construction , a improved back - propagation artifical neural network is used to predict the level displacement and lateral displacement of timbering stake . nonlinear regression prediction of deformation has been achieved
    為了做到信息化施工,以改進的bp人工神經(jīng)網(wǎng)絡(luò)為基礎(chǔ),建立了支護樁水平位移和側(cè)向位移的預(yù)測模型,實現(xiàn)對基坑變形的非線性預(yù)測。
  5. The flood and drought in both first stage and second stage of rainy season in fujian province were forecasted by the ways of line regression prediction equation and three kinds of artificial neural network models , the results show : the backpropagation ( bp ) , radial basis function ( rbf ) and elman neural network models are much better than line regression prediction equation in historical sample fittings , independent sample test , actual prediction ability
    ( 3 )運用線性回歸預(yù)報方程和三種人工神經(jīng)網(wǎng)絡(luò)模型對福建汛期旱澇進行預(yù)測的實驗表明： bp 、徑向基( rbf )和elman這三種人工神經(jīng)網(wǎng)絡(luò)模型在歷史樣本擬合精度上、獨立樣本檢驗結(jié)果和網(wǎng)絡(luò)模型的實際預(yù)測能力上都明顯優(yōu)于傳統(tǒng)的線性回歸方法。

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