Estimation methods of nonlinear regression initial parameter values for rubber material properties prediction

Guowei Liang*, Jingli Xu, Yan Liu, Danyong Wang, Shuhu Li

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The accurate evaluation of rubber material properties is an important means to ensure the safe use of rubber products. Most of the relationships between rubber characteristic index and time are nonlinear regression models, and the estimation of the initial fitting parameters is an important subject in nonlinear regression analysis. In this paper, several methods of evaluating the initial values of nonlinear regression parameters are studied, and a problem of evaluating the aging properties of rubber materials is solved by applying these principles.

Original languageEnglish
Title of host publicationInternational Conference on Mathematics and Machine Learning, ICMML 2023
PublisherAssociation for Computing Machinery
Pages64-67
Number of pages4
ISBN (Electronic)9798400716973
DOIs
Publication statusPublished - 24 Nov 2023
Externally publishedYes
Event2023 International Conference on Mathematics and Machine Learning, ICMML 2023 - Nanjing, China
Duration: 24 Nov 202326 Nov 2023

Publication series

NameACM International Conference Proceeding Series

Conference

Conference2023 International Conference on Mathematics and Machine Learning, ICMML 2023
Country/TerritoryChina
CityNanjing
Period24/11/2326/11/23

Keywords

  • Estimation methods
  • rubber materials
  • the initial fitting parameters
  • the nonlinear regression

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