The Entropy-Based Time Domain Feature Extraction for Online Concept Drift Detection. - Fengqian Ding; Chao Luo 001 (Entropy, 2019)

An Adaptive Financial Trading System Using Deep Reinforcement Learning With Candlestick Decomposing Features. - Fengqian Ding; Chao Luo 001 (IEEE Access, 2020)

Structured sparsity learning for large-scale fuzzy cognitive maps. - Fengqian Ding; Chao Luo 001 (Eng. Appl. Artif. Intell., 2021)

Interpretable cognitive learning with spatial attention for high-volatility time series prediction. - Fengqian Ding; Chao Luo 001 (Appl. Soft Comput., 2022)

Multi-scale temporal features extraction based graph convolutional network with attention for multivariate time series prediction. - Yawen Chen; Fengqian Ding; Linbo Zhai (Expert Syst. Appl., 2022)

Time series prediction based on high-order intuitionistic fuzzy cognitive maps with variational mode decomposition. - Xixi Yao; Fengqian Ding; Luo Chao 001 (Soft Comput., 2022)

Bridging pre-trained models to continual learning: A hypernetwork based framework with parameter-efficient fine-tuning techniques. - Fengqian Ding; Chen Xu; Han Liu; Bin Zhou; Hongchao Zhou (Inf. Sci., 2024)

Multi-scale patch transformer with adaptive decomposition for carbon emissions forecasting. - Xiang Li; Lei Chu; Yujun Li; Fengqian Ding; Zhenzhen Quan; Fangx Qu; Zhanjun Xing (Eng. Appl. Artif. Intell., 2025)

ALAD: A New Unsupervised Time Series Anomaly Detection Paradigm Based on Activation Learning. - Fengqian Ding; Bo Li; Xianye Ben; Jia Zhao; Hongchao Zhou (IEEE Trans. Big Data, 2025)

Spatial-temporal fuzzy cognitive maps based on adaptive graph learning for multivariate time series interpretable prediction. - Jiacheng Tang; Fengqian Ding; Rui Shao; Luo Chao (Appl. Intell., 2025)