絕對誤差 的英文怎麼說

中文拼音 [juéduìwùchā]
絕對誤差 英文
a olute 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...
  • 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 computational results of the particle images are agreement with the simulated datain reasonable, the most absolute difference of the displacement is 0. 6671 pixel at the x abscissa and 0. 7928 pixel at y abscissa ; the computational results are equal to the data form the algorithm of particle brightness - distribution pattern tracking ( the conventional cross - correlation algorithm ) at voluminous points, their discrepancy is only one pixel at few points, mostly in boundary area

    西安理工大學碩士學位論文最後，在visualfortran環境下給出了這種演算法的具體實現，處理模擬粒子圖像的結果與模擬數據比較吻合，最大位移絕對誤差在x方向是0 . 6671像素，在y方向是0 . 7928像素;計算結果與示蹤粒子灰度分佈模板法（基本的互相關法）在絕大部分點是相同的，只在少數點相差一個像素，而且大多出現在邊界區域。
  2. 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。
  3. Compared with the classical bp algorithm, robust adaptive bp algorithm possesses some advantages as following : ( 1 ) increasing the accuracy of the network training by means of using both the relative and absolute residual to adjust the weight values ; ( 2 ) improve the robustness and the network convergence rate through combining with the robust statistic technique by way of judging the values of the samples " relative residual to establish the energy function so that can suppress the effect on network training because of the samples with high noise disturbances ; ( 3 ) prevent entrapping into the local minima area and obtain the global optimal result owing to setting the learning rate to be the function of the errors and the error gradients when network is trained. the learning rate of the weights update change with the error values of the network adaptively so that can easily get rid of the disadvantage of the classical bp algorithm that is liable to entrap into the local minima areas

    與基本bp演算法相比，本文提出的魯棒自適應bp演算法具有以下優點： （ 1 ）與魯棒統計技術相結合，通過訓練樣本相對偏差的大小，確定不同訓練樣本對能量函數的貢獻，來抑制含高噪聲干擾樣本對網路訓練的不良影響，從而增強訓練的魯棒性，提高網路訓練的收斂速度； （ 2 ）採用相對偏差和絕對偏差兩種偏差形式對權值進行調整，提高了網路的訓練精度； （ 3 ）在採用梯度下降演算法對權值進行調整的基礎上，通過將學習速率設為訓練誤差及誤差梯度的特殊函數，使學習速率依賴于網路訓練時誤差瞬時的變化而自適應的改變，從而可以克服基本bp演算法容易陷入局部極小區域的弊端，使訓練過程能夠很快的「跳出」局部極小區域而達到全局最優。
  4. The difference of two methods is relatively small and data of velocity accord preferably, the least absolute error is about 0. 001m / s and the least relative error is 0. 49 % in no boundary position, absolute error is big in the boundary positions which arouse measurement error

    將數值模擬的結果和數字圖像處理的結果相比較分析，發現兩種方法之間的速度差別較小，在非邊界點處兩種方法的速度數據符合相對較好，最小絕對誤差為0 . oolm / s ，最小相對誤差為0 . 49 % 。
  5. In the second part, we adopt a few typical error analysis methods, primarily including the relativity analysis and the regression analysis, to analyses the relative error and absolute error of the time error, spatial data error and statistic data error of the raw input data in the model. then, we take each influence factors in the model into the relativity analysis and the regression analysis. finally, we synthesize the results of the above error analysis to figure out the theoretic accuracy of that model as 87 %

    第二部分主要是採用幾種典型的誤差分析方法，主要包括相關性分析和回歸分析，對模型的原始輸入數據的時間誤差、空間誤差和統計數據誤差進行了相對誤差和絕對誤差的分析，然後又對模型中各影響因子進行了相關分析和回歸分析，最後綜合以上誤差分析的結果得出該模型的理論精度為87 。
  6. 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。
  7. 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 % 。
  8. We would rather have several small absolute errors than one large one.

    我們寧願要幾個小的絕對誤差，而不要一個很大的誤差。
  9. Absolute error of measurement

    測量的絕對誤差
  10. Gives a calculation formula of the absolute error of specific frictional head losses

    給出了湍流區沿程阻力系數絕對誤差的計算式。
  11. Combining absolute error function with relative error function, and setting it as the objective function of bp networks application to the flood forecast

    綜合絕對誤差函數和相對誤差函數於一體，提出一種適合於水文研究的bp神經網路綜合目標函數。
  12. It has been proved in many examples that the bp algorithm based in the square sum of the relative error is better than the conventional bp method

    通過大量算例檢驗證實，在基於相對誤差平方和為檢驗標準前提下，利用所給演算法求得的擬合值或預報結果優于傳統的基於絕對誤差平方和作為目標函數的bp演算法所得結果。
  13. 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 。
  14. This aberration is referred to as a “ m ” by finite element method. rms of absolute error ( rmsa ) is obtained according to displacement, moreover, the relationship graph between rmsa and pressure offers gist for controlling surface precission

    由位移計算出絕對誤差的均方根誤差（ rmsa ） ，得到氣壓與rmsa為非線性的變化關系，其關系圖為通過控制氣壓來調節反射面的精度提供了依據。
  15. 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 。
  16. 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 。
  17. This paper first analyzes performance criteria of a control system, and proposes a controller design method that incorporates disturbance attenuation and robust performance. the robust pid controller design amounts to an optimization problem with a non - convex constraint. genetic algorithm is used to solve the problem due to its global search ability, simulation examples show that the method is effective and have general sense

    本文從分析控制系統的性能指標入手，從抗干擾性能和魯棒性能兩方面綜合考慮控制器的設計，得到一種魯棒pid控制器的設計思路，把pid控制器的設計問題轉化為求解一個帶魯棒性能約束的絕對誤差積分指標（ iae ）優化問題。
  18. 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 。
  19. 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。
  20. Based on a thorough investigation on positional variances of quality control points of jacket, absolute error ellipse and relative error ellipse, which can show the precision of quality control points of jacket in any direction, are presented and then applied to quality control of jacket

    在對質量控制點的點位方差進行深入研究的基礎上，給出表示導管架質量控制點在任意方向上精度的絕對誤差橢圓和相對誤差橢圓，進而將這兩種誤差橢圓應用於導管架的質量控制中，從而使導管架的質量控制更有效和準確。
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