絕對平均誤差 的英文怎麼說

中文拼音 [juéduìpíngjūnwùchā]
絕對平均誤差 英文
absolute average error
  • 絕 : Ⅰ動詞（斷絕） cut off; sever Ⅱ形容詞1 （完全沒有了; 窮盡; 凈盡） exhausted; used up; finished 2 ...
  • 對 : Ⅰ動詞1 （回答） answer; reply 2 （對待; 對付） treat; cope with; counter 3 （朝; 向; 面對） be tr...
  • 平 : Ⅰ形容詞1 （沒有高低凹凸 不頃斜） flat; level; even; smooth 2 （高度相同; 不相上下） on the same l...
  • 均 : Ⅰ形容詞（均勻） equal; even Ⅱ副詞（都; 全） without exception; all
  • 誤 : Ⅰ名詞（錯誤） mistake; error Ⅱ動詞1 （弄錯） mistake; misunderstand 2 （耽誤） miss 3 （使受損害...
  • 差 : 差Ⅰ名詞1 （不相同; 不相合） difference; dissimilarity 2 （差錯） mistake 3 [數學] （差數） differ...
  • 絕對 : absolute
  • 誤差 : error
  1. The most important criteria that used to check the calibrated model are root mean square error ( rms ), the mean absolute error normalized rms error, and mass balance

    模型參數使用試錯法識別，識別過程中最重要的指標是均方差、平均絕對誤差、標準均方差和水均衡。
  2. During the course of the research, the criterions of the interpolation effect are mean error ( me ), mean absolute error ( mae ), root mean squared interpolation error ( rmse ) and the difference of mean square deviation between the measured and the estimated surface air temperature. the conclusions are as follows : ( 1 ) by contrasting the gaussian weighted model associated with the error modification with the gaussian weighted model, the error modification is proved to considerably ameliorate the precision of spatial interpolation ; ( 2 ) on the base of the gaussian weighted model, taking altitudinal effect into account can reflect the trend in which temperature changes according to the topographic altitude and may ameliorate the precision of spatial interpolation correspondingly and apparently, which indicates that topographical effect on the preciseness of spatial interpolation can not be disregarded in terms of the region with complicated topography ; ( 3 ) the map of daily surface air temperature distribution, using the modified gaussian weighted model a and b, can accurately reflect the temperature - changing - with - topographical - altitude trend. among them, the better is the model a, whose me is below 0. 03 ?

    在此過程中，採用平均誤差（ me ） ，平均絕對誤差（ mae ） ，插值平均誤差平方的平方根（ rootmeansquaredinterpolationerror ，簡稱rmsie ） ，插值前後測站要素值的均方差（ meansquaredeviation ，簡稱msd ）差值作為判定插值效果的標準，得出如下結論：通過高斯權重法與結合逐步訂正的高斯權重法的對比，說明結合逐步訂正方案的高斯權重法可大大提高地面日氣溫的插值精度；在高斯權重法中加入海拔影響項可以反映出溫度隨地形高度的變化趨勢，同時也能較大地提高地面日氣溫的空間插值精度，說明在地形復雜的區域，地形影響在插值精度中是不可忽略的；對于高斯權重法的兩種改進方案得到的地面日氣溫分布圖都能很好地反映出表面大氣氣溫隨地形高度的變化趨勢。
  3. Wavelet transform, i. e. multi - resolution decomposition and reconstruction is also used to reduce noise

    與數據未經濾波直接訓練網路相比，預測結果的平均絕對相對誤差降低了3 . 31 % 。
  4. Results show that the rbfnn is obviously superior to the traditional linear model, and its mae ( mean absolute error ) and rmse ( root mean square error ) are 41. 8 and 55. 7, respectively

    結果顯示，該模型預測效果明顯優于傳統的線性自回歸預測模型，各月平均的平均絕對誤差（ mae ）和均方誤差（ rmse ）達到41 . 8和55 . 7 。
  5. Temperature predicting ann model for the next 24 hours is established. by this method, mean absolute error ( mae ) is reduced to 0. 4512 ? from 0. 6663 ? that is calculated by improved ashrae calculation method

    建立了溫度24小時提前預測的人工神經網路模型，使得24小時提前逐時溫度預測平均絕對誤差從改進ashrae計算方法的0 . 6663降低到了0 . 4512 ，平均相對誤差從2 . 02降低到了1 . 36 。
  6. Mae of hourly load prediction reduced to 65. 07kwh and eep reduced to 2. 60 %. this kind of model has not been reported by literature. a cost - minimum model for ice storage system is established and numerical calculation is carried out

    建立了空調逐時負荷的24小時提前預測多點輸出動態模型，更進一步提高了負荷預測的精度，使得逐時負荷預測平均絕對誤差降低到了65 . 07kwh ，期望相對誤差降低到了2 . 60 。
  7. And with simulation result, the author evaluates the accuracy of all kinds of models above - mentioned through mape r and z. the result indicates simulating accuracy of ann model is better than any other models above - mentioned

    並對各種模型模擬結果用mape （絕對平均誤差） 、 r （相關系數） 、 z （輸出數據可信度） 3個精度評價參數來評價模型的精確度，結果表明神經網路模型的模擬精度比其他的模型好。
  8. According to the research results from som model, 8 sub neural network is adopted in inner and mae of hourly cooling load prediction is reduced 80. 64kwh. expected error percentage ( eep ) is reduced to 3. 27 %. next 24 hours hourly cooling load prediction multi - output dynamic model is established and prediction accuracy is improved again

    建立了一個統一的空調逐時負荷的24小時提前人工神經網路預測模型，並根據對日冷負荷類型的som分類結果，通過在內部一共採用8個子神經網路模型使得逐時負荷預測平均絕對誤差降低到了80 . 64kwh ，期望相對誤差降低到了3 . 27 。
  9. With range of r. v. represents the error limit, accuracy or uncertainty of a measurement, the corresponding probability represents the confidence level of the error limit or uncertainty

    若機變數絕對值小於等於一特定范圍代表相對於一量測平均值之誤差范圍，則對應之機率即代表該量測誤差范圍之信心度。
  10. The calibration of flow model is acceptable with average rms of 0. 7m, residual mean of - 0. 045 m, average absolute mean error of 0. 1 m and normalized rms value of 2. 3 %. the contour map of the simulated heads, elaborated acceptable model calibration compared to observed heads map

    模型結果中，均方差為0 . 7m ，平均誤差為- 0 . 045m ，平均絕對誤差為0 . 1m ，標準均方差為2 . 3 ，模擬地下水流場與實際觀測地下水流場基本一致，說明所建立的數值模型符合該地區的實際水文地質條件。
  11. One is combined with the maximum average error criterion and the mean square error criterion, and the other is combined with the absolute value average error criterion and the mean square error criterion. theory analysis shows that the two new search methods have less computational complexity than that of the non - optimal method

    提出了兩種替換原有均方誤差最小準測的方法，分別是最大平均誤差與均方誤差最小準則相結合的搜索標準，以及絕對值平均誤差與均方誤差最小準則相結合的搜索標準。
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