A probabilistic forecasting method based on Quantile Regression Minimal Gated Memory Network and Kernel Density Estimation is proposed in the paper, which is available at this link(https://doi.org/10.1016/j.enconman.2019.06.024).
If the paper or code is helpful to you, please refer to our paper.
[1] Z. Zhang, H. Qin, Y. Liu, L. Yao, X. Yu, J. Lu, Z. Jiang, Z. Feng. Wind speed forecasting based on Quantile Regression Minimal Gated Memory Network and Kernel Density Estimation. Energy Conversion and Management, 2019, 196:1395-1409. DOI: 10.1016/j.enconman.2019.06.024
The introduction in Chinese can refer to my blog. https://blog.csdn.net/m0_37728157/article/details/99874173
note: (1) Due to the confidentiality of the data, the data used in the code is slightly different from the original data in the paper. (2) This code is the python version, and will only be maintained in python.