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(cuò)法識別,識別過程中最重要的指標(biāo)是均方差、平均絕對誤差、標(biāo)準(zhǔn)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(zhǔn)則不能準(zhǔn)確地放映一些灰度圖像主要敏感細(xì)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(yù)測效果明顯優(yōu)于傳統(tǒng)的線性自回歸預(yù)測模型,各月平均的平均絕對誤差( mae )和均方誤差( rmse )達(dá)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(diǎn)集之后,提出一種基于對齊度準(zhǔn)則和根均方誤差的兩步匹配算法完成同名控制點(diǎn)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(chǔ)上,提出了針對相位權(quán)重角度超分辨法的雷達(dá)目標(biāo)的運(yùn)動(dòng)補(bǔ)償方法,分析了雷達(dá)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(dòng)目標(biāo)和有抖動(dòng)目標(biāo)在不同信噪比下的方位估計(jì)誤差和方位超分辨的信噪比門限進(jìn)行了仿真計(jì)算,并將結(jié)果同波束空間music方法及cramerrao限進(jìn)行了比較。