Abstract：Outlier data will affect the fitting accuracy of the regression model in data analysis,especially the high-dimensional uncertain outlier data.The fuzzy regression method can reduce the impact of outliers on the fitting of multidimensional data models.In this paper,a fuzzy residual algorithm is proposed.First,a fuzzy regression model is constructed in the fuzzy domain,and then iteratively calculates the residual between the observed value and the estimated value to determine the weight.The model parameters are estimated by minimizing the weighted objective function,and a robust fuzzy regression model based on weighted optimization is obtained.The final model fits the target data more accurately.Simulation results show that under the influence of outliers,compared with RTS-L1 algorithm and FLAR algorithm,fuzzy residual algorithm has better estimation accuracy and robustness.
刘云,郑文凤,张轶. 模糊残差算法对离群点数据的优化研究[J]. 小型微型计算机系统, 2021, 42(6): 1321-1326.
LIU Yun,ZHENG Wen-feng,ZHANG Yi. Optimization of Outlier Data by Fuzzy Residual Algorithm. Journal of Chinese Computer Systems, 2021, 42(6): 1321-1326.
2021, Vol. 42 
