Bingqing Peng — accepted AI-conference papers

2024

WeatherGNN: Exploiting Meteo- and Spatial-Dependencies for Local Numerical Weather Prediction Bias-Correction

Binqing Wu, Weiqi Chen, Wengwei Wang, Bingqing Peng, Liang Sun, Ling Chen

IJCAI 2024poster

Due to insufficient local area information, numerical weather prediction (NWP) may yield biases for specific areas. Previous studies correct biases mainly by employing handcrafted features or applying data-driven methods intuitively, overlooking the complicated dependencies between weather factors a…

Cited by 6 Source ↗PDF ↗Scholar ↗

2023

eForecaster: Unifying Electricity Forecasting with Robust, Flexible, and Explainable Machine Learning Algorithms

Zhaoyang Zhu, Weiqi Chen, Rui Xia, Tian Zhou, Peisong Niu, Bingqing Peng +5

AAAI 2023technical

Electricity forecasting is crucial in scheduling and planning of future electric load, so as to improve the reliability and safeness of the power grid. Despite recent developments of forecasting algorithms in the machine learning community, there is a lack of general and advanced algorithms specific…

Cited by 5 Source ↗PDF ↗Scholar ↗