A data-driven model based on Fourier transform and support vector regression for monthly reservoir inflow forecasting

By Xiang Yu, Xueqing Zhang, Hui Qin. 2018

67 citations recorded by the source corpus.

Subfields: Electrical and Electronic Engineering, Environmental Engineering, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/e145d25b7dda8b9ef94227fa57845891d87f3950

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Electrical and Electronic Engineering

1. Xiangang Luo
2. Shuang Zhu
3. Lingsheng Meng
4. Xiaohui Yuan
5. Jing Peng
6. Zhanya Xu

In Environmental Engineering

1. Xiangang Luo
2. Shuang Zhu
3. Lingsheng Meng
4. Xiaohui Yuan
5. Jing Peng
6. Zhanya Xu

In Global and Planetary Change

1. Xiangang Luo
2. Shuang Zhu
3. Lingsheng Meng
4. Xiaohui Yuan
5. Jing Peng
6. Zhanya Xu

Citations in the corpus

• A hybrid support vector regression framework for streamflow forecast (2019, background): “Accurate streamflow forecasting is of significant importance for planning and management of water resources, as well as early warning and mitigation of natural disasters such as droughts and floods (Yu et al., 2018).”