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(shù)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。
The popular fidelity measurement method based on root mean squared error ( rmse ) is unable to completely reflect the details of the sensitive information of compressed grayscale images 摘要常用的基于均方根誤差( rmse )圖像保真度準則不能準確地放映一些灰度圖像主要敏感細節(jié)。
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(jié)果顯示,該模型預測效果明顯優(yōu)于傳統(tǒng)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 。
When feature point sets are extracted respectively from the two images , correspondence between the point sets is then established by a two - stage matching algorithm . this matching algorithm is based on the alignment metric and < wp = 4 > rmse ( root mean square error ) 對兩幅圖像分別提取廣義特征點集之后,提出一種基于對齊度準則和根均方誤差的兩步匹配算法完成同名控制點的建立。
The motion compensation of radar target and an analysis of influence of component imperfection in the realization of the method are presented . to evaluate the performance of the proposed method . monte carlo simulation has been conducted to estimate the root mean square error of the angle estimates and the spatial resolution snr threshold in the cases of both non - fluctuating targets and fluctuating targets 在此基礎上,提出了針對相位權(quán)重角度超分辨法的雷達目標的運動補償方法,分析了雷達系統(tǒng)各部件的不理想性對超分辨性能的影響,用montecarlo方法對無抖動目標和有抖動目標在不同信噪比下的方位估計誤差和方位超分辨的信噪比門限進行了仿真計算,并將結(jié)果同波束空間music方法及cramerrao限進行了比較。