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Troubleshooting in geoelectrical prospecting using real‐coded genetic algorithm with chromosomal extrapolation
Author(s) -
Calixto Wesley Pacheco,
Paulo Coimbra A.,
Mota Jesus Carlos da,
Wu Marcel,
Silva Wander G.,
Alvarenga Bernardo,
Brito Leonardo da Cunha,
Alves Aylton Jose,
Domingues Elder Geraldo,
Neto Daywes Pinheiro
Publication year - 2014
Publication title -
international journal of numerical modelling: electronic networks, devices and fields
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.249
H-Index - 30
eISSN - 1099-1204
pISSN - 0894-3370
DOI - 10.1002/jnm.1986
Subject(s) - extrapolation , prospection , operator (biology) , prospecting , genetic algorithm , troubleshooting , algorithm , population , computer science , data mining , mathematics , statistics , machine learning , engineering , geography , mining engineering , biology , archaeology , demography , repressor , sociology , transcription factor , gene , operating system , biochemistry
SUMMARY This work presents a genetic operator developed from mathematical methods of curve extrapolation applied in solving problems in geoelectrical prospection. This operator will assist the production of fitter individuals in the population of a genetic algorithm in which inherent patterns of the best individuals of each generation are recognized. The proposed operator in conjunction with a real‐coded genetic algorithm is compared to five alternative optimization techniques known and used in the application to problems in geoelectrical prospection. Copyright © 2014 John Wiley & Sons, Ltd.