均方根误差

词组短语

root mean square error

与均方根误差相关的网络例句 [注：此内容来源于网络，仅供参考]

The simulation results demonstrate that the proposed algorithm can effectively reduce the location estimation error and variance of the MS, and has favorable performance in both root mean square error and mean error cumulative distribution function.

仿真结果表明，该算法能有效降低移动台位置估计的误差和方差，具有良好的均方根误差和均值误差CDF性能。

Prediction results of indepe ndent and dependent samples show that the RMS errors of SSTA predicted in 10～12 months ahead are smaller than SSTA mean square deviation and that the relative e rrors in 5 months ahead are less than 50%.

经检验，对于非独立和独立样本，预报的均方根误差分别在12个月和1 0个月预报时效内小于SSTA的均方差，相对误差在5个月预报时效内都小于50％。

The simulation result shows that this dynamical prediction model has the performances like, better generalization, stronger robust, and preferable accuracy (the relative root mean square error of air is lower than 10%, and the relative root mean square error of oxygen is lower than 19%).

仿真研究结果表明：该动态预估模型具有较好的泛化能力和较强的鲁棒性，并具有较好预测精度(风量预测的相对均方根误差小于10%，氧量预测的相对均方根误差小于19%)。

It was found that the predicted results of the mathematic model are good when the number of samples is 15 in calibration model and that in validation model is 6 (the total is 21) In that case, the value of the root mean square error of the estimation of calibration and the root mean square error of prediction of validation are very small(0.0115 and 0.0105 respectively) and almost the same.

结果发现，当校正集样品数为15检验集样品数为6（总样品数为21）时，使用外部检验法建立的数学模型预测结果较好，其校正集的均方根误差和检验集的预测均方根误差（分别为RMSEE和RMSEP）均较小（分别为0.0115和0.0105），而且很接近。

The model was built by partial least squareregress.Compared to the model using the whole original spectra,the root mean square error of predictionof glycerol gonolaurate and lubricant was improved from 7.9557 to 6.6787,and 0.2383 to 0.1031 respectively.(4)In uninformative variable eliminationalgorithm,the cutoff threshold of UVE is evaluated by adding a noise matrix which size is the same with instrumental response data.

提出的方法应用于月挂酸成分预测的红外光谱和机油分类的可见-近红外光谱中，用偏最小二乘回归建立模型，相比于用全光谱建立的模型，月挂酸的成分预测均方根误差分别从7.9557提高到6.6787，机油分类的成分预测均方根误差从0.2383提高到

Results In static phantom studies, the percent error of mean activity obtained by Carson's method was reduced to about 9 %, and it is less than that of image-derived method using maximum likelihood expectation maximization (about 14 %). In simulated dynamic phantom studies, the vessel component could be extracted using ICA in image and sinogram domain. In sinogram domain, the six components extracted by ICA could be obtained quickly.

在静态物理假体实验结果来看，使用Carson's method计算出感兴趣区域活性的百分比误差( 9%)比直接从影像取得活性的百分比误差( 14%)来得小；从数位模拟动态假体实验结果来看，独立成份分析法运用在影像空间或是弦波图空间上，都可以将血管分离出来，但从弦波图空间上得到各个独立成份相对於影像空间就快得多；imageICA和sinogramICA计算出的输入函数的标准化均方根误差分别是0.57和0.28。

The experiments were carried out to calibrate FDR in the lab and field, and calibration equations were verified by oven-dried method for soil samples obtained by augers. The result showed that good calibrating equations with average RMSE 0.023 m^3/m^3 were fitted in the lab, but they had poor RMSE 0.066 m^3/m^3 when used in the field. Other calibrating equations with average RMSE 0.026 m^3/m^3 were also fitted by indirect field calibration method, and they had good RMSE 0.026 m^3/m^3 when used in the field.

结果表明，室内试验获得了较好的模型参数，均方根误差平均达到了0.023 立方公尺/立方公尺，但是应用到田间条件下误差很大，均方根误差平均为0.066立方公尺/立方公尺；田间条件下也间接获得了较好的模型参数，均方根误差的平均值为0.026立方公尺/立方公尺，应用于田间时测定含水量的精确度较高，均方根误差的平均值为0.026立方公尺/立方公尺。

For total absorption coefficient at 443 nm (a443), the root-mean-square-error is 0.046 in the South China Sea, with an averaged percentage error of 7.9%, and averaged error in log scale close to 0. For coastal waters off Fujian, RMSE, an averaged percentage error and δ are 0.194, 30.6%, and -0.167, respectively.

对于443 nm的总吸收系数（a443 ），南海的对数均方根误差为0.046，平均相对误差为7.9%，对数平均偏差为0；福建沿岸水体的对数均方根误差为0.194，平均相对误差为30.6%，对数平均偏差为-0.167 。

Finally, in additional to the comparison of results derived by PPP and DGPS, they were all compared to Anping tide gauge records as well. The aim of this study is the analysis of height variations provided by different methodologies. Comparing to Anping tide gauge records, the differences in height variations can achieve 4.5 cm with DGPS; 6 cm with final product; 10 cm with rapid product; 25 cm with ultra-rapid product; 1~2 m with ultra-rapid product.

实验中也搜集了安平潮位站的潮位资料，故也将此资料与GPS浮标高程方向定位成果进行比较，而研究中将著重於高程变化量之分析，假设潮位仪观测海水面高程变化量为参考解，由实验结果可发现差分相对定位椭球高变化量均方根误差之平均值约4.5公分；使用最终产品时椭球高变化量均方根误差之平均值可以达到6公分以内；使用快速产品时椭球高变化量均方根误差之平均值可以达到10公分以内；使用超快速产品观测部分於观测环境理想时椭球高变化量均方根误差之平均值可以达到25公分左右；使用超快速产品预估部分时椭球高变化量均方根误差之平均值约1~2公尺。

In this study, six campaigns around Anping tide gauge, Tainan, were successfully performed and the collected GPS buoy data were processed with four types of precise ephemeris provided by IGS, including final product, rapid product, ultra-rapid product and ultra-rapid product with the use of PPP technique. Comparing the PPP results with DGPS, the differences reach 3~5 cm in the horizontal and 10 cm in the vertical with final product; 6~8 cm in the horizontal and 15 cm in the vertical with rapid product; 15~20 cm in the horizontal and 30~40 cm in the vertical with ultra-rapid product; 2~3 m in the horizontal and 3~4 m in the vertical with ultra-rapid product. In addition, the collected data were also processed by DGPS techniques using different reference stations to analyze the effect of various baselines. The results show that accuracy degrades when the baselines increase.

本研究在台南安平潮位站旁进行6次GPS浮标施测，首先利用与GPS浮标距离不同之GPS参考主站来进行差分定位，分析基线距离对GPS浮标定位成果的影响，由实验结果可得出基线越长则定位准确度越低；再以IGS提供之最终产品、快速产品、超快速产品(Ultra-Rapid product)之观测部分observed half、超快速产品(Ultra-Rapid product)之预估部分四种不同发布延迟时间的精密星历与精密时表改正资料对GPS浮标进行精密单点定位解算，与传统差分相对定位方法定位结果进行比较后，得出使用最终产品之平面方向均方根误差(Root Mean Square Error， RMSE)可达3~5公分，而高程方向均方根误差可达10公分；快速产品之平面方向均方根误差可达6~8公分，而高程方向均方根误差可达15公分；超快速产品观测部分之平面方向均方根误差可达15~20公分，而高程方向均方根误差可达30~40公分；超快速产品预估部分之平面方向均方根误差可达2~3公尺，而高程方向均方根误差可达3~4公尺。

与均方根误差相关的网络解释 [注：此内容来源于网络，仅供参考]

root-mean-square misfit：均方根拟合差

root-mean-square error 均方根误差 | root-mean-square misfit 均方根拟合差 | root-mean-square value 均方根值

root mean square error：均方根误差

交易者的影响可能微乎其微.这为市场波动研究提供了更明确的研究对象.从HAR-RRV和HAR-RV的样本内预测分析中可以看到预测结果的精度仍然是已实现极差比已实现波动要好,均方根误差(root mean square error),绝对误差平均(mean absolute error),

RMSE Root Mean Square Error：均方根误差

RMS Router Management Service 路由器管理服务 | RMSE Root Mean Square Error 均方根误差 | RMX Remote MultipleXer 远端复用器

Root Mean Square error, RMSE：均方根误差 平均平方誤差

■ roll back 回滚 ロールバック | ■ Root Mean Square error, RMSE 均方根误差 平均平方誤差 | ■ route link 路由链路 ルートリンク

Root Mean Square error, RMSE：均方根误差

Risk 风险 | Root mean square error (RMSE) 均方根误差 | Routing problems 路径问题

root-mean-square deviation：均方根差

root-mean-square criterion 均方根判别准则 | root-mean-square deviation 均方根差 | root-mean-square error 均方根误差

root-mean-square criterion：均方根准则,均方根判别准则,均方根误差准则

root-mean-square (rms) pulse duration 均方根脉冲持续时间,均方根脉冲持续时间 | root-mean-square criterion 均方根准则,均方根判别准则,均方根误差准则 | root-mean-square current 均方根电流

root-mean-square current：均方根面

root mean square 均方根 | root mean-square current 均方根面 | root mean-square error 均方根误差

mean-square error criterion：均方根误差准则

手段目的分析 means-end analysis | 均方根误差准则 mean-square error criterion | 故障间平均置换 mean-swap-between-failure

rms error：均方根误差

ritz formula 里兹公式 | rms error 均方根误差 | rna 核糖核酸