Publications

TFCAD: Time–Frequency Causal Anomaly Detection for Multivariate Time Series

Wenxuan He, Mingjing Du*, Wenbin Zhang. TFCAD: Time–Frequency Causal Anomaly Detection for Multivariate Time Series. Information Processing and Management, 2027, 64(2): 105120.

DPIA: Dynamic periodic interaction and adaptation for multivariate time series forecasting

Cheng Tan, Wenbin Zhang, Mingjing Du*. DPIA: Dynamic Periodic Interaction and Adaptation for Multivariate Time Series Forecasting. Pattern Recognition, 2026, 180: 114310.

AFGBStream: Adaptive Fuzzy Granular-BallFramework for Stream Clustering with Sliding Windows

Qijia Wang, Mingjing Du*, Weiping Ding. AFGBStream: Adaptive Fuzzy Granular-BallFramework for Stream Clustering with Sliding Windows. IEEE Transactions on Fuzzy Systems, 2026, 34(8): 2529–2541.

Adaptive Representation Learning Framework for IncompleteMulti-View Clustering

Yawen He, Mingjing Du*. Adaptive Representation Learning Framework for IncompleteMulti-View Clustering. Information Sciences, 2026, 715: 123588.

Time-frequency augmented multi-level contrastive clustering for time series

Congyu Wang, Mingjing Du*, Xiang Jiang. Time-frequency augmented multi-level contrastive clustering for time series. Proceedings of the AAAI Conference on Artificial Intelligence, 2026, 40(31): 26142-26150.

Structure-aware granular ball clustering

Qijia Wang, Mingjing Du*. Structure-aware granular ball clustering. Information Sciences, 2026, 740: 123224.

RFAG: Random forest clustering based on anchor graph

Jinyu Li, Congyu Wang, Mingjing Du*. RFAG: Random forest clustering based on anchor graph. Pattern Recognition, 2026, 174: 112997.

Fuzzy cluster-aware contrastive clustering for time series

Congyu Wang, Mingjing Du*, Xiang Jiang, Yongquan Dong*. Fuzzy cluster-aware contrastive clustering for time series. Pattern Recognition, 2026, 173: 112899.

GDCMAD: Graph-based dual-contrastive representation learning for multivariate time series anomaly detection

Sheng He, Wenxuan He, Mingjing Du*, Xiang Jiang, Yongquan Dong*. GDCMAD: Graph-based dual-contrastive representation learning for multivariate time series anomaly detection. Information Sciences, 2026, 728: 122790.

Contrastive learning-based multi-view clustering for incomplete multivariate timeseries

Yurui Li, Mingjing Du^*, Xiang Jiang, Nan Zhang. Contrastive learning-based multi-view clustering for incomplete multivariate timeseries. Information Fusion, 2025, 117: 102812.

Efficient online stream clustering based on fast peeling of boundary micro-cluster

Jiarui Sun, Mingjing Du^*, Chen Sun, Yongquan Dong. Efficient online stream clustering based on fast peeling of boundary micro-cluster. IEEE Transactions on Neural Networks and Learning Systems, 2025, 36(3): 5680 - 5693.

Feature weighting-based deep fuzzy C-Means for clustering incomplete time series

Yurui Li, Mingjing Du^*, Wenbin Zhang, Xiang Jiang, Yongquan Dong. Feature weighting-based deep fuzzy C-Means for clustering incomplete time series. IEEE Transactions on Fuzzy Systems, 2024, 32 (12): 6835 - 6847.

Erosion clustering

Mingjing Du^*, Fuyu Wu, Yurui Li, Yongquan Dong.Erosion clustering. Acta Electronica Sinica, 2024, 52(10): 3459-3471.

TWStream: Three-way stream clustering

Jiarui Sun, Mingjing Du^*, Zhenkang Lew, Yongquan Dong. TWStream: Three-way stream clustering. IEEE Transactions on Fuzzy Systems 2024, 32(9): 4927-4939.

Density-based clustering with differential privacy

Fuyu Wu, Mingjing Du^*, Qiang Zhi. Density-based clustering with differential privacy. Information Sciences, 2024, 68: 121211

VAEAT: Variational AutoeEncoder with adversarial training for multivariate time series anomaly detection

Sheng He, Mingjing Du^*, Xiang Jiang, Wenbin Zhang, Congyu Wang. VAEAT: Variational AutoeEncoder with adversarial training for multivariate time series anomaly detection. Information Sciences, 2024, 676: 120852.

M3W: Multistep three-way clustering

Mingjing Du^*, Jingqi Zhao, Jiarui Sun, Yongquan Dong.M3W: Multistep three-way clustering. IEEE Transactions on Neural Networks and Learning Systems, 2024, 35(4): 5627-5640.

A three-way clustering method based on improved density peaks algorithm and boundary detection graph

Chen Sun, Mingjing Du^*, Jiarui Sun, Kangkang Li, Yongquan Dong. A three-way clustering method based on improved density peaks algorithm and boundary detection graph. International Journal of Approximate Reasoning, 2023, 153: 239-257., 2023.

Grid-based clustering using boundary detection

Mingjing Du^*, Fuyu Wu. Grid-based clustering using boundary detection. Entropy, 2022, 24(11): 1606.

ROBP: a robust border-peeling clustering using Cauchy kernel

Mingjing Du^*, Ru Wang, Ru Ji, Xia Wang, Yongquan Dong. ROBP: a robust border-peeling clustering using Cauchy kernel. Information Sciences, 2021, 571: 375-400.

A novel density peaks clustering with sensitivity of local density and density-adaptive metric

Mingjing Du, Shifei Ding, Yu Xue, Zhongzhi Shi. A novel density peaks clustering with sensitivity of local density and density-adaptive metric. Knowledge and Information Systems, 2019, 59(2): 285-309.

Density peaks clustering using geodesic distances

Mingjing Du, Shifei Ding, Xiao Xu, Yu Xue. Density peaks clustering using geodesic distances. International Journal of Machine Learning and Cybernetics, 2018, 9(8): 1335-1349.

A robust density peaks clustering algorithm using fuzzy neighborhood

Mingjing Du, Shifei Ding, Yu Xue. A robust density peaks clustering algorithm using fuzzy neighborhood. International Journal of Machine Learning and Cybernetics, 2018, 9(7): 1131-1140.

An entropy-based density peaks clustering algorithm for mixed type data employing fuzzy neighborhood

Shifei Ding, Mingjing Du, Tongfeng Sun, Xiao Xu, Yu Xue. An entropy-based density peaks clustering algorithm for mixed type data employing fuzzy neighborhood. Knowledge-Based Systems, 2017, 133: 294-313.

A novel density peaks clustering algorithm for mixed data

Mingjing Du, Shifei Ding, Xue Yu. A novel density peaks clustering algorithm for mixed data. Pattern Recognition Letters, 2017, 97: 46-53.

Study on density peaks clustering based on k-nearest neighbors and principal component analysis

Mingjing Du, Shifei Ding, Hongjie Jia. Study on density peaks clustering based on k-nearest neighbors and principal component analysis. Knowledge-Based Systems, 2016, 99: 135-145.

Survey on granularity clustering

Shifei Ding, Mingjing Du, Hong Zhu. Survey on granularity clustering. Cognitive Neurodynamics, 2015, 9(6): 561-572.

* Corresponding author

# Equal authorship