GPLAB A Genetic Programming Toolbox for MATLAB

By Sara Silva. 2004

353 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/5b0b9e5380466f330580c422b64ec32af91c1037

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Amir H. Gandomi
2. Amir Hossein Alavi
3. Mathieu Vrac
4. A. Casanueva
5. Renate A. I. Wilcke
6. M. Widmann
7. J. Gutiérrez
8. R. Benestad

Citations in the corpus

• Energy-based numerical models for assessment of soil liquefaction (2012, methodology): “GPLAB (Silva 2007), in conjunction with subroutines coded in MATLAB, was used to implement the tree-based GP algorithm.”
• An intercomparison of a large ensemble of statistical downscaling methods over Europe: Results from the VALUE perfect predictor cross‐validation experiment (2016, methodology): “The MOGP code is based on the strength Pareto evolutionary algorithm (SPEA) by Zitzler and Thiele (1999) and the GPLAB by Silva and Almeida (2003).”
• Estimating Saturated Hydraulic Conductivity Using Genetic Programming (2007, methodology): “SSSAJ: Volume 71: Number 6  November –December 2007 1679 In this study, the GP system used is an adaptation of GPLAB ( Silva, 2007 ), a GP toolbox for MATLAB.”
• Modelling the dynamics of the evapotranspiration process using genetic programming (2007, methodology): “The various GP parameters adopted in this study are given in Table 1. In this study, the GP system used is an adaptation of GPLAB ( Silva, 2005 ), a GP toolbox for MATLAB.”