A new fuzzy regression algorithm

被引：42

作者：

Pop, HF

Sarbu, C

机构：

[1] BABES BOLYAI UNIV,FAC CHEM,R-3400 CLUJ NAPOCA,ROMANIA

[2] BABES BOLYAI UNIV,FAC MATH & COMP SCI,R-3400 CLUJ NAPOCA,ROMANIA

来源：

ANALYTICAL CHEMISTRY | 1996年 / 68卷 / 05期

关键词：

D O I：

10.1021/ac950549u

中图分类号：

O65 [分析化学];

学科分类号：

070302 ; 081704 ;

摘要：

A new fuzzy regression algorithm is described and compared with conventional ordinary and weighted least-squares and robust regression methods. The application of these different methods to relevant data sets proves that the performance of the procedure described in this paper exceeds that of the ordinary least-squares method and equals and often exceeds that of weighted or robust methods, including the two fuzzy methods proposed previously (Otto, M.; Bandemer, H., Chemom. Intell. Lab. Syst, 1986, 1, 71. Hu, Y.; Smeyers-Verbeke, J.; Massart, D. L. Chemom, Intell, Lab. Syst, 1990, 8, 143), Moreover, we emphasize the effectiveness and the generality of the two new criteria proposed in this paper for diagnosing the linearity of calibration lines in analytical chemistry.

引用

页码：771 / 778

页数：8

共 35 条

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