Meta-heuristic to estimate parameters in Non-Linear Regression Models
by K. Antony Arokia Durai Raj, B. Kanagasabapathi, Gopichand Agnihothram
International Journal of Mathematics in Operational Research (IJMOR), Vol. 3, No. 5, 2011

Abstract: Non-Linear Regression Models (NLRM) are used in analysing scientific applications such as metal treatment, chemical process, pharmacology, and physiology. If the parameters in a regression model are non-linear, then the model is termed as NLRM, even if the explanatory variables of such a model are linear. The computational effort required to solve linear regression models are less compared to NLRMs. In this paper we propose a Genetic Algorithm (GA) to estimate the parameters in NLRMs. The computational results show that the proposed GA performs better than/equivalent to the existing methods in most of the problem instances considered in this study.

Online publication date: Thu, 12-Feb-2015

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