Genetic Programming MATLAB Toolbox

版本 1.0.0.0 (224.5 KB) 作者: Janos Abonyi
This method results in more robust and interpretable models than the classical GP method
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更新时间 2014/7/10

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Linear-in-parameters models are quite widespread in process engineering, e.g. NAARX, polynomial ARMA models, etc. Genetic Programming (GP) is able to generate nonlinear input-output models of dynamical systems that are represented in a tree structure. This GP-OLS toolbox applies Orthogonal Least Squares algorithm (OLS) to estimate the contribution of the branches of the tree to the accuracy of the model. This method results in more robust and interpretable models than the classical GP method.

Papers about the application of this toolbox:
J. Madar, J. Abonyi, F. Szeifert, Genetic Programming for the Identification of Nonlinear Input-Output Models, Industrial & Engineering Chemistry Research, 44, 3178-3186, 2005

For more MATLAB tools please visit:
http://www.abonyilab.com/software-and-data

Html help:
http://www.abonyilab.com/software-and-data/gp_index/gpols

引用格式

Janos Abonyi (2024). Genetic Programming MATLAB Toolbox (https://www.mathworks.com/matlabcentral/fileexchange/47197-genetic-programming-matlab-toolbox), MATLAB Central File Exchange. 检索来源 .

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版本 已发布 发行说明
1.0.0.0