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Application of genetic programming in symbolic regression

Detian Yan

Abstract

Genetic programming(GP)is a kind of mathematical programming method based on Darwin's theory of evolution.The application of GP in symbolic regression is discussed.No fitting function form for data fitting is needed while running GP and global optimum can be gotten with reasonable cross and mutation probability.The fitting for a arbitrary curve is impossible with conventional method,while with GP it is easy to implement.Examples are given to explain data fitting of measurement by GP.

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Available abstract

Key concepts: Symbolic regression, Genetic programming, Curve fitting, Darwin (ADL), Computer science, Genetic algorithm, Algorithm, Function (biology)