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马福民

作者: 院办 日期: 2018-09-04 浏览次数:

[1]马福民*,等.基于Zipf分布的网格密度峰值聚类算法[J].控制与决策, 2024, 39(2): 577-587.

[2]Fumin Ma, et.al. Key Grids Based Batch-incremental CLIQUE Clustering Algorithm Considering Cluster Structure Changes[J]. Information Sciences, 660 (2024): 120109.

[3] T Zhang, Y Zhang,Fumin Ma*, et.al. Local Boundary Fuzzified Rough K-means Based Information Granulation Algorithm Under the Principle of Justifiable Granularity. IEEE Transactions on Cybernetics. 2024, 54(1): 519-532.

[4] T Zhang,Fumin Ma*, et.al. Interval Type-2 Fuzzy Local Enhancement Based Rough K-means Clustering Considering Imbalanced Clusters. IEEE Transactions on Fuzzy Systems. 2020, 28(9): 1925-1939.

[5]Fumin Ma*, et.al. Compressed Binary Discernibility Matrix Based Incremental Attribute Reduction Algorithm for Group Dynamic Data, Neurocomputing, 2019, 344: 20-27.

[6]马福民*,等.考虑边界样本邻域归属信息的粗糙K-Means增量聚类算法[J].控制与决策, 2022, 37(11): 2968-2976.

[7]Fumin Ma*, et.al. Rough K-prototypes Clustering Algorithm Based on OTC Similarity and Between-Cluster Information for Mixed Data[C]. Chinese Control and Decision Conference, 2022, pp. 5105-5111.

[8] T Zhang*, C Lv,Fumin Ma*, K Zhao, H Wang, Gregory M.P. O'Hare. A Photovoltaic Power Forecasting Model Based on Dendritic Neuron Networks with the Aid of Wavelet Transform[J]. Neurocomputing, 2020, 397(15): 438-446.

[9]张鑫涛,马福民*,等.基于混合度量与类簇自适应调整的粗糙模糊K-means聚类算法[J],模式识别与人工智能,2019, 32(12): 1141-1150.

[10] X Zhou,Fumin Ma*, M Zhang. Clustering Ensemble Algorithm Based on an Improved Co-association Matrix [C]. Intelligent Computing for Sustainable Energy and Environment, 2021, pp. 805-815.

[11]Fumin Ma*, TengfeiZhang. Generalized Binary Discernibility Matrix for Attribute Reduction in Incomplete Information Systems,The Journal of China Universities of Posts and Telecommunications, 2017, 24(4): 57-68.

[12]] T Zhang,Fumin Ma*, C Peng, Y Yu, D Yue, C Dou, Gregory M.P. O'Hare. A Very-Short-Term Online PV Power Forecasting Model Based on RAN with Secondary Dynamic Adjustment[J]. IEEE Transactions on Artificial Intelligence. 2023, 4(5): 1214-1224.

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