Mapping the spatial distributions of oxide abundances and Mg# on the lunar surface using multi-source data and a new ensemble learning algorithm-Reference-Cited by-同舟云学术

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Mapping the spatial distributions of oxide abundances and Mg# on the lunar surface using multi-source data and a new ensemble learning algorithm

Published:2024-06 Issue: Volume:245 Page:105894
ISSN:0032-0633
Container-title:Planetary and Space Science
language:en
Short-container-title:Planetary and Space Science

Author:

Bian Chaofa,Zhang Kefei,Wu Yunzhao,Wu Suqin,Lu Yu,Shi Hongtao,Li Huaizhan,Zhao Dongsheng,Duan Yabo,Zhao Ling,Wu Huajing

Funder

State Key Laboratory of Geo-Information Engineering

National Natural Science Foundation of China

Publisher

Elsevier BV

Reference51 articles.

1. Comparison of regression models under multi-collinearity;Bagya Lakshmi;Electronic Journal of Applied Statistical Analysis,2018

2. Global mapping of lunar refractory elements: multivariate regression vs. machine learning;Bhatt;Astron. Astrophys.,2019

3. Prediction of field-scale wheat yield using machine learning method and multi-spectral UAV data;Bian;Rem. Sens.,2022

4. Age and composition of young basalts on the Moon, measured from samples returned by Chang'E-5;Che;Science.,2021

5. XGBoost: A Scalable Tree Boosting System;Chen,2016

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Global Inversion of Lunar Surface Oxides by Adding Chang’e-5 Samples;Remote Sensing;2024-05-20

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