RegressÃo simbÃlica via programaÃÃo genÃtica: um estudo de caso com modelagem geofÃsica

AUTOR(ES)
DATA DE PUBLICAÇÃO

2006

RESUMO

Symbolic regression, which is in principal the handling of mathematical expressions for finding a function that describes a data set, was until recently carried out exclusively by humans. But now, several computational techniques of symbolic regression automatization have appeared. One of these techniques is genetic programming, a subarea of evolutive computing that uses an analogy to Darwinâs evolutionary theory and some ideas from the Genetics field to develop a group of computer programs in a search for solutions to computational tasks. This work aims to test the symbolic regression capabilities of genetic programming with the objective of verifying its viability as a tool for a specific geophysical research. This research concerns phenomena that occurs in the ionosphere, the region of earthâs atmosphere ionized by the action of solar rays, that play a fundamental role in telecommunications. In the course of this trial, we used two implementations of traditional genetic programming and one implementation of a variant, named gene expression programming. Problems like the one under study demand a lot of processor time and are memory consuming, therefore, the work culminates with a distributed implementation of genetic programming with the objective of accelerating the modeling process.

ASSUNTO(S)

programaÃÃo da expressÃo gÃnica genetic programming ciencia da computacao programaÃÃo genÃtica symbolic regression geophisical modeling regressÃo simbÃlica modelagem geofÃsica gene expression programming programaÃÃo genÃtica (computaÃÃo)

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