Improving flood forecasting through feature selection by a genetic algorithm – experiments based on real data from an Amazon rainforest river-Reference-Cited by-同舟云学术

Improving flood forecasting through feature selection by a genetic algorithm – experiments based on real data from an Amazon rainforest river

Published:2020-10-03 Issue:1 Volume:14 Page:37-50
ISSN:1865-0473
Container-title:Earth Science Informatics
language:en
Short-container-title:Earth Sci Inform

Author:

Vieira Alen Costa,Garcia Gabriel,Pabón Rosa E. C.,Cota Luciano P.,de Souza Paulo,Ueyama Jó,Pessin Gustavo^ORCID

Publisher

Springer Science and Business Media LLC

Subject

General Earth and Planetary Sciences

Link

https://link.springer.com/content/pdf/10.1007/s12145-020-00528-8.pdf

Reference39 articles.

1. Bhandari D, Murthy CA (1996) Genetic algorithm with elitist model and its convergence. IJPRAI 10(6):731–747

2. Chen ST, Yu PS (2007) Pruning of support vector networks on flood forecasting. J Hydrol 347(1):67–78

3. de Lucena DV, de Lima TW, Soares AS, Coelho CJ (2012) Multi-objective evolutionary algorithm nsga-ii for variables selection in multivariate calibration problems. Int J Natural Comput Res 3:43–58

4. de Oliveira LL, Freitas AA, Tinós R. (2018) Multi-objective genetic algorithms in the study of the genetic code’s adaptability. Inf Sci 425:48–61

5. de Paula TI (2015) Avaliação da influência de parêmetros do algoritmo genético na otimização de um problema multiobjetivo utilizando-se arranjo de misturas. Master’s thesis, PPGEP, Univesidade Federal de Itajubá

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