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2篇 您的检索式:作者名="Yanghong Zhang Feng Sun"
    题名 作者 年代 出处 被引量
1Comparative Variance and Multiple Imputation Used for Missing Values in Land Price DataSet显示文摘Based on the two-dimensional relation table,this paper studies the missing values in the sample data of land price of Shunde District of Foshan City.GeoDa software was used to eliminate the insignificant factors by stepwise regression analysis;NORM software was adopted to construct the multiple imputation models;EM algorithm and the augmentation algorithm were applied to fit multiple linear regression equations to construct five different filling datasets.Statistical analysis is performed on the imputation data set in order to calculate the mean and variance of each data set,and the weight is determined according to the differences.Finally,comprehensive integration is implemented to achieve the imputation expression of missing values.The results showed that in the three missing cases where the PRICE variable was missing and the deletion rate was 5%,the PRICE variable was missing and the deletion rate was 10%,and the PRICE variable and the CBD variable were both missing.The new method compared to the traditional multiple filling methods of true value closer ratio is 75%to 25%,62.5%to 37.5%,100%to 0%.Therefore,the new method is obviously better than the traditional multiple imputation methods,and the missing value data estimated by the new method bears certain reference value.Longqing Zhang Xinwei Zhang Liping Bai Yanghong Zhang Feng Sun Changcheng Chen 2019Computers, Materials & Continua2019,,9:1
2Difference of Visual Information Metric Based on Entropy of Primitive显示文摘Image sparse representation is a method of efficient compression and coding of image signal in the process of digital image processing.Image after sparse representation,to enhance the transmission efficiency of the image signal.Entropy of Primitive(EoP)is a statistical representation of the sparse representation of the image,which indicates the probability of each base element.Based on the EoP,this paper presents an image quality evaluation method-Difference of Visual Information Metric(DVIM).The principle of this method is to evaluate the image quality with the difference between the original image and the distorted image.The comparative experiments between DVIM&PSNR&SSIM are carried out.It was found that there was a great improvement in the image quality evaluation of geometric changes.This method is an effective image quality evaluation method,which overcomes the weakness of other quality evaluation methods for geometrically changing images to a certain extent,and is more consistent with the subjective observation of the human eye.Yanghong Zhang Feng Sun Liwei Tian Jinfeng Li Longqing Zhang Shengfu Lan 2020Computers, Materials & Continua2020,,2:0
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