Author:
Zhao Yangyang,Niu Wei,Wang Meinan
Reference6 articles.
1. Chen, C., Shi, L.Z., Gao, J., et al.: Aircraft fuel flow prediction based on QAR data. Control Eng. 4, 752–758 (2019). (Chinese)
2. Li, D., Peng, J., He, D.: Aero-engine exhaust gas temperature prediction based on LightGBM optimized by improved bat algorithm. Therm. Sci. 25(2 Part A), 845–858 (2021)
3. Xu, B.Q., He, J.C., Sun, L.Z.: Fault detection method of cage asynchronous motor based on stacked autoencoder and improved LightGBM algorithm [J/OL]. Electric Mach. Control, 1–7 (2021). http://kns.cnki.net/kcms/detail/23.1408.TM.20210408.1517.004.html
4. Ke, G., et al.: The LightGBM: a highly efficient gradient boosting decision tree. In: Proceedings of the 31st Conference on Neural Information Processing Systems, Long Beach, California, USA, pp. 3146–3154 (2017)
5. Chen, T., Guestrin, C.: XGBoost: a scalable tree boosting system. In: ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (2016)