DEC-GEP Tool:A Gene expression programming Matlab tools

DEC-GEP tool was developed for data-driven symbolic regression applications.

This tool was developed for data-driven symbolic regression applications. The DEC-GEP optimizes a complete genotype of expression trees for mathematical model synthesis with their constant coefficients from a training dataset. To illustrate an application of the DEC-GEP algorithm in a real-world data-driven modeling application, a symbolic regression model for the soft calibration of e-nose (the low-cost, solid state multisensor array measurements) is shown. You can define your custom functions and operators in DEC-GEP. This tool allows users to seamlessly integrate a wide range of optimization techniques, leveraging MATLAB's flexible environment. The flexibility of MATLAB’s framework enables users to customize optimization strategies according to their specific problem requirements, adjusting parameters, constraints, and objective functions as needed. This is particularly valuable in multidisciplinary applications, where optimization problems may vary widely in form and complexity. The ability to integrate custom algorithms or adapt existing ones allows for highly tailored solutions, improving the efficiency and effectiveness of the optimization process.