An eXtreme Gradient Boosting Algorithm Combining Artificial Bee Colony Parameters Optimized Technique for Single Sand Body Identification

Due to the problems of traditional artificial single sand body identification methods such as strong subjectivity, heavy workload and low efficiency, we propose a fast and objective ABC-XGBoost. The algorithm consists of two parts: eXtreme gradient boosting (XGBoost) and artificial bee colony algori...

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Detalles Bibliográficos
Autores principales:	Renze Luo, Liang Guo, Xingyu Li, Juanjuan Tuo, Canru Lei, Yang Zhou
Formato:	article
Lenguaje:	EN
Publicado:	IEEE 2021
Materias:	Single sand body identification artificial bee colony algorithm machine learning eXtreme gradient boosting ABC-XGBoost Electrical engineering. Electronics. Nuclear engineering TK1-9971
Acceso en línea:	https://doaj.org/article/3101e991a6bd4b168f74f5c264897432
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An eXtreme Gradient Boosting Algorithm Combining Artificial Bee Colony Parameters Optimized Technique for Single Sand Body Identification

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