Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Genetic programming: an introduction: on the automatic evolution of computer programs and its applications
Robust symbolic regression with affine arithmetic
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Symbolic regression using nearest neighbor indexing
Proceedings of the 12th annual conference companion on Genetic and evolutionary computation
'Identifying the structure of nonlinear dynamic systems using multiobjective genetic programming
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
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This paper presents a comparative study of the Multi-Branches Genetic Programming (MBGP), GP-NARMAX model approach and Standard Genetic Programming (SGP) for modelling problems. Sunspots data have been considered as study case in order to performance this comparison. The main point is to generate mathematical models in a polynomial form; thus the root node for MBGP has been set as the addition operator. Results show that MBGP rapidly evolves towards good mathematical models which are also easily to translate as well as the GP-NARMAX approach represented in its polynomial form in contrast to SGP.