A new spline approach for data fitting

被引：9

作者：

Nunhez, JR ^{[1
]}

Costa, CBB ^{[1
]}

Guirardello, R ^{[1
]}

机构：

[1] Univ Estadual Campinas, UNICAMP, Fac Engn Quim, Dept Proc Quim, BR-13083970 Campinas, SP, Brazil

来源：

FLUID PHASE EQUILIBRIA | 2004年 / 220卷 / 02期

基金：

巴西圣保罗研究基金会;

关键词：

data fitting; thermodynamic data; spline method; maximun likelihood principle;

D O I：

10.1016/j.fluid.2004.04.003

中图分类号：

O414.1 [热力学];

学科分类号：

摘要：

This paper presents an extension of the Modified Spline Technique (MST) formulation for data fitting named power spline, which gives consistent results for sets of data of concave and convex curves. This method is based on a technique which couples an implicit formulation of the maximum likelihood principle to the spline method, making the method suitable to fit data when no physical model is available. The MST method proved to be better than to the spline method and the extended spline fit technique (EST), because it provided accurate results for the first and second derivatives in sets of data where the EST solution developed inaccuracies. The EST method is a formulation that couples Least Squares to the spline method. There are, however, some sets of data where the MST method would show inconsistent solutions for the first and second derivatives. The power spline method eliminates these problems for concave or convex curves. Another improvement on the method is a more flexible choice for the interval boundaries.' (C) 2004 Elsevier B.V. All rights reserved.

引用

页码：171 / 180

页数：10

共 9 条

[1]

[Anonymous], 1988, Optimization of chemical processes

[2] ESTIMATION OF PARAMETERS IN NONLINEAR, IMPLICIT MODELS [J].