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

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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Bibliographic Details
Main Authors: Renze Luo, Liang Guo, Xingyu Li, Juanjuan Tuo, Canru Lei, Yang Zhou
Format: article
Language:EN
Published: IEEE 2021
Subjects:
Single sand body identification
artificial bee colony algorithm
machine learning
eXtreme gradient boosting
ABC-XGBoost
Electrical engineering. Electronics. Nuclear engineering
TK1-9971
Online Access:https://doaj.org/article/3101e991a6bd4b168f74f5c264897432
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https://doaj.org/article/3101e991a6bd4b168f74f5c264897432

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