XGB Model : Research on Evaporation Duct Height Prediction Based on XGBoost Algorithm
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Date
2020-04
Authors
Zhao, Wenpeng
Li, Jincai
Zhao, Jun
Zhao, Dandan
Lu, Jingze
Wang, Xiang
ORCID
Advisor
Referee
Mark
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Volume Title
Publisher
Společnost pro radioelektronické inženýrství
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Abstract
Evaporation duct is a specific atmospheric structure at sea, which has an important influence on the propagation path of electromagnetic waves (EW). Considering the limit of existing evaporation duct height (EDH) prediction models and aiming at prpoposing more accurate and stronger generalization ability of EDH models, we applied eXtreme Gradient Boosting (XGBoosting) algorithm to the field of evaporation duct for the first time. And we proposed the new EDH prediction model using XGBoost algorithm(XGB model). Simultaneously, traditional Paulus-Jeske (PJ) model and deep learning Multilayer Perceptron (MLP) model were introduced into the experiment to make a comparison. In terms of comprehensive performance, XGB model is optimal in all sub-regions and total area. Finally, cross-learning experiments were carried out to test the generalization ability of XGB model. The results show that the generalization ability of XGB model is better than that of MLP model.
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Citation
Radioengineering. 2020 vol. 29, č. 1, s. 81-93. ISSN 1210-2512
https://www.radioeng.cz/fulltexts/2019/20_01_0081_0093.pdf
https://www.radioeng.cz/fulltexts/2019/20_01_0081_0093.pdf
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Peer-reviewed
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en