Funder
Российский Фонд Фундаментальных Исследований
Министерство науки и высшего образования Российской Федерации
Publisher
Springer Science and Business Media LLC
Subject
General Earth and Planetary Sciences
Reference33 articles.
1. Bergstra JS, Bardenet R, Bengio Y, Kegl B (2011) Algorithms for hyper-parameter optimization. Advances in neural information processing systems: 2546–2554. https://hal.inria.fr/hal-00642998
2. Breiman L (2001) Random forests. Mach Learn 45(1):5–32. https://doi.org/10.1023/A:1010933404324
3. Cander LR, Milosavljevic MM, Stankovic SS, Tomasevic S (1998) Ionospheric forecasting technique by artificial neural network. Electron Lett 34(16):1573–1574. https://doi.org/10.1049/el:19981113
4. Cesaroni C, Spogli L, Aragon-Angel A, Fiocca M, Dear V, De Franceschi G, Romano V (2020) Neural network based model for global total electron content forecasting. J Space Weather Space Clim 10:11. https://doi.org/10.1051/swsc/2020013
5. Chen T, Guestrin C (2016) Xgboost: a scalable tree boosting system. In: Proceedings of the 22nd ACM SIGKDD international conference on knowledge discovery and data mining, pp 785–794. https://doi.org/10.1145/2939672.2939785
Cited by
41 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