Fengqian Ding

According to our database, Fengqian Ding authored at least 13 papers between 2019 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

PFEAL: A Novel Framework for Image Anomaly Detection Using Pre-Trained Feature Extraction and Activation Learning.

Fengqian Ding, Bo Li, Han Liu, Chuandong Lyu, Xianye Ben, Hongchao Zhou

IEEE Trans. Emerg. Top. Comput. Intell., February, 2026

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., August, 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, June, 2025

Spatio-Temporal Anomaly Detection for 5G-Clusters: A Multi-Scale Fuzzy Contrastive Learning Approach.

Chao Luo, Yinghua Li, Fengqian Ding, Rui Shao

IEEE Trans. Netw., 2025

Global-local coherency contrastive learning for context-aware time series forecasting.

Fengqian Ding, Chen Xu, Han Liu, Chuandong Lyu, Gangqiang Yang, Hailiang Xiong, Hongchao Zhou

Knowl. Based Syst., 2025

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

2024

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

2022

Time series prediction based on high-order intuitionistic fuzzy cognitive maps with variational mode decomposition.

Xixi Yao, Fengqian Ding, Luo Chao

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

Interpretable cognitive learning with spatial attention for high-volatility time series prediction.

Fengqian Ding, Chao Luo

Appl. Soft Comput., 2022

2021

Structured sparsity learning for large-scale fuzzy cognitive maps.

Fengqian Ding, Chao Luo

Eng. Appl. Artif. Intell., 2021

2020

An Adaptive Financial Trading System Using Deep Reinforcement Learning With Candlestick Decomposing Features.

Fengqian Ding, Chao Luo

IEEE Access, 2020

2019

The Entropy-Based Time Domain Feature Extraction for Online Concept Drift Detection.

Fengqian Ding, Chao Luo

Entropy, 2019