TS_XGB: Ultra-Short-Term Wind Power Forecasting Method Based on Fusion of Time-Spatial Data and XGBoost Algorithm. - Jiading Jiang; Feng Wang; Rui Tang; Lingling Zhang; Xin Xu (ITQM, 2021)

Research on Ultra-Short-Term Wind Power Forecasting Based on Refactored Representation of Environmental Features. - Feng Wang; Jiading Jiang; Lingling Zhang (WI/IAT (Workshop/Special Session), 2021)

Carbon trading price forecasting: based on improved deep learning method. - Feng Wang; Jiading Jiang; Junyi Shu (ITQM, 2022)

Augmenting the diversity of imbalanced datasets via multi-vector stochastic exploration oversampling. - Hongrui Li; Shuangxin Wang; Jiading Jiang; Chuiyi Deng; Junmei Ou; Ziang Zhou; Dingli Yu (Neurocomputing, 2024)

Handling data heterogeneity for wind turbine fault diagnosis via dynamic ensemble multilevel interactive learning. - Shuangxin Wang; Hongrui Li; Jiading Jiang; Meng Li; Junmei Ou; Dingli Yu (Eng. Appl. Artif. Intell., 2025)