JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE) ›› 2026, Vol. 61 ›› Issue (1): 49-64.doi: 10.6040/j.issn.1671-9352.4.2025.004
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| [1] IKOTUN A M, EZUGWU A E, ABUALIGAH L, et al. k-means clustering algorithms: a comprehensive review, variants analysis, and advances in the era of big data[J]. Information Sciences, 2023, 622:178-210. [2] D'ANDRADE R G. U-statistic hierarchical clustering[J]. Psychometrika, 1978, 43(1):59-67. [3] BEZDEK J C. Patternrecognition with fuzzy objective function algorithms[J]. Advanced Applications in Pattern Recognition,1981, 22(1171):203-239. [4] MIRKIN B. Mathematical classification and clustering[M]. New York: Springer, 2013:3-7. [5] HORNG Y J, CHEN S M, CHANG Y C, et al. A new method for fuzzy information retrieval based on fuzzy hierarchical clustering and fuzzy inference techniques[J]. IEEE Transactions on Fuzzy Systems, 2005, 13(2):216-228 [6] QUINTANA F J, GETZ G, HED G, et al. Cluster analysis of human autoantibody reactivities in health and in type 1 diabetes mellitus: a bioinformatic approach to immune complexity[J]. Autoimmunity, 2003, 21(1):65-75. [7] GENTHER H, GLESNER M. Advanced data preprocessing using fuzzy clustering techniques[J]. Fuzzy Sets and Systems, 1997, 85(2):155-164. [8] QIAO Xiaoguang, CHEN Caikou, WANG Weiye. Efficient subspace clustering and feature extraction vial l-norm and l-norm minimization[J]. Neurocomputing, 2024, 595:127813. [9] CHOI S, YOON S. Change-point model-based clustering for urban building energy analysis[J]. Renewable and Sustainable Energy Reviews, 2024, 199:114514. [10] SCHAFFER M, VERA-VALDÉS J E, MARSZAL-POMIANOWSKA A, et al. Exploring smart heat meter data: a co-clustering driven approach to analyse the energy use of single-family houses[J]. Applied Energy, 2024, 371:123586. [11] GÓMEZ-FLORES W, HERNÁNDEZ-LÓPEZ J. Automatic adjustment of the pulse-coupled neural network hyperparameters based on differential evolution and cluster validity index for image segmentation[J]. Applied Soft Computing, 2020, 97:105547. [12] LIAO Jiyong, WU Xingjiao, WU Yaxin, et al. K-NNDP: k-means algorithm based on nearest neighbor density peak optimization and outlier removal[J]. Knowledge-Based Systems, 2024, 294:111742. [13] HEIDARI J, DANESHPOUR N, ZANGENEH A. A novel k-means and k-medoids algorithms for clustering non-spherical-shape clusters non-sensitive to outliers[J]. Pattern Recognition, 2024, 155:110639. [14] CAO Xinyu, YU Min, ZHANG Shuming, et al. Hierarchical clustering evolutionary tree-support for SLA[J]. Journal of Manufacturing Processes, 2024, 125:189-201. [15] XU Zeshui, WU Junjie. Intuitionistic fuzzy c-means clustering algorithms[J]. Journal of Systems Engineering and Electronics, 2010, 21(4):580-590. [16] SHANG Taotao, HUANG Qianwen, WANG Yongyi. Vibration reduction and energy harvesting on the ship thrust bearing unit excited by a measured shaft longitudinal vibration using NES-GMM[J]. Ocean Engineering, 2024, 294:116914. [17] LIN Rongfu, GUO Weizhong, CHENG Shing Shin. Type synthesis of novel 1R, 2R, 1R1T, and 2R1T hybrid RCM mechanisms based on topological arrangement and modular design method[J]. Mechanism and Machine Theory, 2024, 200:105692. [18] SZMIDT E, KACPRZYK J. Entropy for intuitionistic fuzzy sets[J]. Fuzzy Sets and Systems, 2001, 118(3):467-477. [19] GUO Kaihong, ZANG Jie. Knowledge measure for interval-valued intuitionistic fuzzy sets and its application to decision making under uncertainty[J]. Soft Computing, 2019, 23:6967-6978. [20] GUO Kaihong, XU Hao. Knowledge measure for intuitionistic fuzzy sets with attitude towards non-specificity[J]. International Journal of Machine Learning and Cybernetics, 2019, 10:1657-1669. [21] PATEL A, JANA S, MAHANTA J. Construction of similarity measure for intuitionistic fuzzy sets and its application in face recognition and software quality evaluation[J]. Expert Systems with Applications, 2024, 237:121491. [22] GUO Kaihong, XU Hao. A unified framework for knowledge measure with application:from fuzzy sets through interval-valued intuitionistic fuzzy sets[J]. Applied Soft Computing, 2021, 109:107539. [23] ZHANG Xiaoyan, WANG Jinghong, HOU Jianglong. Matrix-based approximation dynamic update approach to multi-granulation neighborhood rough sets for intuitionistic fuzzy ordered datasets[J]. Applied Soft Computing, 2024, 163:111915. [24] 陈宝国,邓明. 基于对象更新的邻域多粒度粗糙集模型增量式算法[J]. 智能系统学报,2023,18(3):562-576. CHEN Baoguo, DENG Ming. Incremental algorithm for neighborhood multi-granular rough set model based on object update[J]. Journal of Intelligent Systems, 2023, 18(3):562-576. [25] 莫子孟,尹立平. 基于模糊粗糙集的大型汽轮机组设备故障识别算法[J]. 能源科技,2024,22(3):44-48. MO Zimeng, YIN Liping. Fault diagnosis method for large turbine units based on fuzzy rough set[J]. Energy Technology, 2024, 22(3):44-48. [26] 刘以,张小峰,孙玉娟,等. 基于加权滤波与核度量的鲁棒图像分割算法[J]. 激光与光电子学进展,2024,61(8):380-392. LIU Yi, ZHANG Xiaofeng, SUN Yujuan, et al. Robust image segmentation algorithm based on weighted filtering and kernel metrics[J]. Progress in Laser and Optoelectronics, 2024, 61(8):380-392. [27] 刘子源,马占有,李霞,等.基于模糊测度的最大可能性互模拟等价研究[J/OL]. 郑州大学学报(理学版).(2025-01-13)[2025-11-16]. https://doi.org/10.13705/j.issn.1671-6841.2024144.7. LIU Ziyuan, MA Zhanyou, LI Xia, et al. Study on maximum likelihood mutual simulation equivalence based on fuzzy measures[J/OL]. Journal of Zhengzhou University(Natural Science Edition).(2025-01-13)[2025-11-16]. https://doi.org/10.13705/j.issn.1671-6841.2024144.7. [28] 李繁,张晓宇,刘林东. 基于广义粒度自编码器的模糊粗糙聚类算法[J]. 计算机应用与软件,2024,41(3):266-275. LI Fan, ZHANG Xiaoyu, LIU Lindong. Fuzzy rough clustering method based on generalized granular self-encoder[J]. Computer Applications and Software, 2024, 41(3):266-275. [29] 朱世超,王骋程,王超,等. 基于支持向量聚类和模糊粗糙集的交通流数据修复算法[J]. 森林工程,2023,39(1):157-165. ZHU Sichao, WANG Chengcheng, WANG Chao, et al. Traffic flow data repair method based on support vector clustering and fuzzy rough sets[J]. Forest Engineering, 2023, 39(1):157-165. [30] 任浩伟,王青海,张巧珍. 区间值直觉模糊β覆盖粗糙集模型[J]. 陕西科技大学学报,2024,42(5):214-224. REN Haowei, WANG Qinghai, ZHANG Qiaozhen. Interval-valued intuitionistic fuzzy β-covering rough set model[J]. Journal of Shaanxi University of Science and Technology, 2024, 42(5):214-224. [31] 商钰玲,李鹏,朱枫,等. 基于模糊逻辑的物联网流量攻击检测技术综述[J]. 计算机科学,2024,51(3):3-13. SHANG Yuling, LI Peng, ZHU Feng, et al.Overview of IoT traffic attack detection technology based on fuzzy logic[J]. Computer Science, 2024, 51(3):3-13. [32] ATANASSOV K T. Intuitionistic fuzzy sets[J]. Fuzzy Sets and Systems, 1986, 20(1):87-96. [33] GUO Kaihong, XU Hao. Preference and attitude in parameterized knowledge measure for decision making under uncertainty[J]. Applied Intelligence, 2021, 51(10):7484-7493. [34] MÜLLER K R, MIKA S, RATSCH G, et al. An introduction to kernel-based learning algorithms[J]. IEEE Transactions on Neural Networks, 2001, 12(2):181-201. [35] WAN Jihong, CHEN Hongmei, LI Tianrui, et al. Dynamic interaction feature selection based on fuzzy rough set[J]. Information Sciences, 2021, 581:891-911. [36] MERCER J. Functions of positive and negative type, and their connection with the theory of integral equations[J]. Philosophical Transactions of the Royal Society of London, 1909, 209:415-446. [37] YAGER R R. Some aspects of intuitionistic fuzzy sets[J]. Fuzzy Optimization and Decision Making, 2009, 8(1):67-90. [38] YANG Xiaowei, ZHANG Guangquan, LU Jie, et al. A kernel fuzzyc-means clustering-based fuzzy support vector machine algorithm for classification problems with outliers or noises[J]. IEEE Transactions on Fuzzy Systems, 2010, 19(1):105-115. [39] KASTRITSI T, DOULGERI Z. A controller to impose a RCM for hands-on robotic-assisted minimally invasive surgery[J]. IEEE Transactions on Medical Robotics and Bionics, 2021, 3(2):392-401. [40] PU Yue, YAO Wenbin, LI Xiaoyong. EM-IFCM: fuzzy c-means clustering algorithm based on edge modification for imbalanced data[J]. Information Sciences, 2024, 659:120029. [41] RAN Xingcheng, XI Yue, LU Yonggang, et al. Comprehensive survey on hierarchical clustering algorithms and the recent developments[J]. Artificial Intelligence Review, 2023, 56:8219-8264. [42] YU Hong, WANG Xincheng, WANG Guoyin, et al. An active three-way clustering method via low-rank matrices for multi-view data[J]. Information Sciences, 2020, 507:823-839. [43] LIU Rui, WANG Hong, YU Xiaomei. Shared-nearest-neighbor-based clustering by fast search and find of density peaks[J]. Information Sciences, 2018, 450:200-226. [44] WANG Wei, XIA Feng, NIE Hansong, et al. Vehicle trajectory clustering based on dynamic representation learning of internet of vehicles[J]. IEEE Transactions on Intelligent Transportation Systems, 2020, 22(6):3567-3576. |
| [1] | LI Ling-qiang, LI Qing-guo. The characterizations of lattice-valued fuzzy lower approximation operators by a unique axiom [J]. JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE), 2014, 49(10): 78-82. |