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For: Nazari A, Dehghan A, Nejatian S, Rezaie V, Parvin H. A comprehensive study of clustering ensemble weighting based on cluster quality and diversity. Pattern Anal Applic 2019;22:133-45. [DOI: 10.1007/s10044-017-0676-x] [Cited by in Crossref: 42] [Cited by in F6Publishing: 31] [Article Influence: 7.0] [Reference Citation Analysis]
Number Citing Articles
1 Zarei AR, Mahmoudi MR. Evaluation of the Effect of Changes in Climatic Variables at Different Levels on the Rate of Potential Evapotranspiration in Arid and Semi-Arid Regions. Pure Appl Geophys 2022. [DOI: 10.1007/s00024-022-03207-5] [Reference Citation Analysis]
2 Liu C, Liu S, Osmani A. An ensemble clustering method based on consistency cluster consensus approach and MapReduce model. Trans Emerging Tel Tech 2022. [DOI: 10.1002/ett.4695] [Reference Citation Analysis]
3 Li W, Wang Z, Sun W, Bahrami S. An Ensemble Clustering Framework Based on Hierarchical Clustering Ensemble Selection and Clusters Clustering. Cybernetics and Systems. [DOI: 10.1080/01969722.2022.2073704] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
4 Ansari J, Abbasi AR, Heydari MH, Avazzadeh Z. Simultaneous design of fuzzy PSS and fuzzy STATCOM controllers for power system stability enhancement. Alexandria Engineering Journal 2022;61:2841-50. [DOI: 10.1016/j.aej.2021.08.007] [Cited by in Crossref: 7] [Cited by in F6Publishing: 10] [Article Influence: 7.0] [Reference Citation Analysis]
5 Zhang M. Weighted clustering ensemble: A review. Pattern Recognition 2022;124:108428. [DOI: 10.1016/j.patcog.2021.108428] [Cited by in Crossref: 4] [Cited by in F6Publishing: 3] [Article Influence: 4.0] [Reference Citation Analysis]
6 Huang H, Mei F, Wu Q, Bao Y, Zhang H. The feature extracting method via partitioning the feature subspace and data fusion. 4th International Conference on Informatics Engineering & Information Science (ICIEIS2021) 2022. [DOI: 10.1117/12.2627133] [Reference Citation Analysis]
7 Pho K, Akbarzadeh H, Parvin H, Nejatian S, Alinejad-rokny H. A multi-level consensus function clustering ensemble. Soft Comput 2021;25:13147-13165. [DOI: 10.1007/s00500-021-06092-7] [Cited by in Crossref: 1] [Article Influence: 0.5] [Reference Citation Analysis]
8 Jiang Y, Guo Y, Zhou Y, Li X, Liu S. The Effects of Munsell Neutral Grey Backgrounds on the Colour of Chrysoprase and the Application of AP Clustering to Chrysoprase Colour Grading. Minerals 2021;11:1092. [DOI: 10.3390/min11101092] [Cited by in Crossref: 8] [Cited by in F6Publishing: 8] [Article Influence: 4.0] [Reference Citation Analysis]
9 Zarei AR, Mahmoudi MR, Shabani A. Using the Fuzzy Clustering and Principle Component Analysis for Assessing the Impact of Potential Evapotranspiration Calculation Method On the Modified RDI Index. Water Resour Manage 2021;35:3679-702. [DOI: 10.1007/s11269-021-02910-7] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 2.0] [Reference Citation Analysis]
10 Guo S, Chen M, Abolhassani A, Kalamdani R, Guo WG. Identifying manufacturing operational conditions by physics-based feature extraction and ensemble clustering. Journal of Manufacturing Systems 2021;60:162-75. [DOI: 10.1016/j.jmsy.2021.05.005] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
11 Sun T, Mashdour S, Mahmoudi MR. An Ensemble Clusterer Framework based on Valid and Diverse Basic Small Clusters. Int J Info Tech Dec Mak 2021;20:1189-219. [DOI: 10.1142/s0219622021500309] [Reference Citation Analysis]
12 Lin J, Wu L, Chen R, Wu J, Wang X. Double‐weighted fuzzy clustering with samples and generalized entropy features. Concurrency Computat Pract Exper 2021;33. [DOI: 10.1002/cpe.5758] [Reference Citation Analysis]
13 Dabighi K, Nazari A, Saryazdi S. A step edge detector based on bilinear transformation. IFS 2021;40:3863-74. [DOI: 10.3233/jifs-191229] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
14 Sun L, Wang K, Balezentis T, Streimikiene D, Zhang C. Extreme point bias compensation: A similarity method of functional clustering and its application to the stock market. Expert Systems with Applications 2021;164:113949. [DOI: 10.1016/j.eswa.2020.113949] [Cited by in Crossref: 4] [Cited by in F6Publishing: 3] [Article Influence: 2.0] [Reference Citation Analysis]
15 najafi F, parvin H, mirzaei K, nejatiyan S, rezaie SV; Department of Computer Engineering, Maybod Branch, Islamic Azad University, Department of Computer Engineering, Mamasani Branch, Islamic Azad University, Department of Computer Engineering, Maybod Branch, Islamic Azad University, Department of Electrical Engineering, Yasooj Branch, Islamic Azad University, Department of Electrical Engineering, Yasooj Branch, Islamic Azad University. A new ensemble clustering method based on fuzzy cmeans clustering while maintaining diversity in ensemble. JSDP 2021;17:103-22. [DOI: 10.29252/jsdp.17.4.103] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
16 Kejia S, Parvin H, Qasem SN, Tuan BA, Pho K. A classification model based on svm and fuzzy rough set for network intrusion detection. IFS 2020;39:6801-6817. [DOI: 10.3233/jifs-191621] [Reference Citation Analysis]
17 Tu G, Qin Z, Huo D, Zhang S, Yan A. Fingerprint-based computational models of 5-lipo-oxygenase activating protein inhibitors: Activity prediction and structure clustering. Chem Biol Drug Des 2020;96:931-47. [PMID: 33058463 DOI: 10.1111/cbdd.13657] [Cited by in Crossref: 2] [Cited by in F6Publishing: 3] [Article Influence: 0.7] [Reference Citation Analysis]
18 Wang Z, Parvin H, Qasem SN, Tuan BA, Pho K. Cluster ensemble selection using balanced normalized mutual information. IFS 2020;39:3033-3055. [DOI: 10.3233/jifs-191531] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
19 Ma T, Yu T, Wu X, Cao J, Al-abdulkarim A, Al-dhelaan A, Al-dhelaan M. Multiple clustering and selecting algorithms with combining strategy for selective clustering ensemble. Soft Comput 2020;24:15129-15141. [DOI: 10.1007/s00500-020-05264-1] [Cited by in Crossref: 2] [Article Influence: 0.7] [Reference Citation Analysis]
20 Chang W, Ji X, Liu Y, Xiao Y, Chen B, Liu H, Zhou S. Analysis of University Students’ Behavior Based on a Fusion K-Means Clustering Algorithm. Applied Sciences 2020;10:6566. [DOI: 10.3390/app10186566] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 1.0] [Reference Citation Analysis]
21 Lotfian R, Gholamnejad J, Mirzaeian Lardkeyvan Y. Effective solution of the long-term open pit production planning problem using block clustering. Engineering Optimization 2021;53:1119-34. [DOI: 10.1080/0305215x.2020.1771703] [Cited by in Crossref: 4] [Cited by in F6Publishing: 3] [Article Influence: 1.3] [Reference Citation Analysis]
22 Mahmoudi MR, Akbarzadeh H, Parvin H, Nejatian S, Rezaie V, Alinejad-rokny H. Consensus function based on cluster-wise two level clustering. Artif Intell Rev 2021;54:639-65. [DOI: 10.1007/s10462-020-09862-1] [Cited by in Crossref: 12] [Cited by in F6Publishing: 13] [Article Influence: 4.0] [Reference Citation Analysis]
23 Li G, Mahmoudi MR, Qasem SN, Tuan BA, Pho K. Cluster ensemble of valid small clusters. IFS 2020;39:525-542. [DOI: 10.3233/jifs-191530] [Reference Citation Analysis]
24 Bahrani P, Minaei-bidgoli B, Parvin H, Mirzarezaee M, Keshavarz A, Alinejad-rokny H. User and item profile expansion for dealing with cold start problem. IFS 2020;38:4471-83. [DOI: 10.3233/jifs-191225] [Cited by in Crossref: 10] [Cited by in F6Publishing: 11] [Article Influence: 3.3] [Reference Citation Analysis]
25 Xu W, Parvin H, Izadparast H. Deep Learning Neural Network for Unconventional Images Classification. Neural Process Lett 2020;52:169-85. [DOI: 10.1007/s11063-020-10238-3] [Cited by in Crossref: 9] [Cited by in F6Publishing: 9] [Article Influence: 3.0] [Reference Citation Analysis]
26 Min X, Huang Y, Sheng Y. Automatic Determination of Clustering Centers for “Clustering by Fast Search and Find of Density Peaks”. Mathematical Problems in Engineering 2020;2020:1-11. [DOI: 10.1155/2020/4724150] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 0.3] [Reference Citation Analysis]
27 Najafi F, Parvin H, Mirzaie K, Nejatian S, Rezaie V. Dependability‐based cluster weighting in clustering ensemble. Stat Anal Data Min: The ASA Data Sci Journal 2020;13:151-64. [DOI: 10.1002/sam.11451] [Cited by in Crossref: 6] [Cited by in F6Publishing: 6] [Article Influence: 2.0] [Reference Citation Analysis]
28 Zhang T, Yang Y, Zeng Y, Zhao Y. Cognitive Template-Clustering Improved LineMod for Efficient Multi-object Pose Estimation. Cogn Comput 2020;12:834-43. [DOI: 10.1007/s12559-020-09717-5] [Cited by in Crossref: 7] [Cited by in F6Publishing: 9] [Article Influence: 2.3] [Reference Citation Analysis]
29 Niu H, Khozouie N, Parvin H, Alinejad-rokny H, Beheshti A, Mahmoudi MR. An Ensemble of Locally Reliable Cluster Solutions. Applied Sciences 2020;10:1891. [DOI: 10.3390/app10051891] [Cited by in Crossref: 22] [Cited by in F6Publishing: 21] [Article Influence: 7.3] [Reference Citation Analysis]
30 Özöğür‐akyüz S, Otar BÇ, Atas PK. Ensemble cluster pruning via convex‐concave programming. Computational Intelligence 2020;36:297-319. [DOI: 10.1111/coin.12267] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 0.7] [Reference Citation Analysis]
31 Yang H, Peng H, Zhu J, Nie F. Co-Clustering Ensemble Based on Bilateral K-Means Algorithm. IEEE Access 2020;8:51285-94. [DOI: 10.1109/access.2020.2979915] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 1.0] [Reference Citation Analysis]
32 Diaz C, Galy O, Caillaud C, Yacef K. A Clustering Approach for Modeling and Analyzing Changes in Physical Activity Behaviors From Accelerometers. IEEE Access 2020;8:224123-34. [DOI: 10.1109/access.2020.3044295] [Cited by in Crossref: 4] [Cited by in F6Publishing: 7] [Article Influence: 1.3] [Reference Citation Analysis]
33 Lei Q, Li T. Semi-Supervised Selective Affinity Propagation Ensemble Clustering With Active Constraints. IEEE Access 2020;8:46255-66. [DOI: 10.1109/access.2020.2978404] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 1.0] [Reference Citation Analysis]
34 Ruan X, Ren D, Zhu X, Liu S. Optimized Data Association Based on Gaussian Mixture Model. IEEE Access 2020;8:2590-2598. [DOI: 10.1109/access.2019.2962236] [Reference Citation Analysis]
35 Zhao X, Rao Y, Cai J, Ma W. Abnormal Trajectory Detection Based on a Sparse Subgraph. IEEE Access 2020;8:29987-30000. [DOI: 10.1109/access.2020.2972299] [Cited by in Crossref: 9] [Cited by in F6Publishing: 10] [Article Influence: 3.0] [Reference Citation Analysis]
36 Wang X, Shao C, Xu S, Zhang S, Xu W, Guan Y. Study on the Location of Private Clinics Based on K-Means Clustering Method and an Integrated Evaluation Model. IEEE Access 2020;8:23069-81. [DOI: 10.1109/access.2020.2967797] [Cited by in Crossref: 5] [Cited by in F6Publishing: 6] [Article Influence: 1.7] [Reference Citation Analysis]
37 Li Y, Guo C, Sun L. Fast Clustering by Affinity Propagation Based on Density Peaks. IEEE Access 2020;8:138884-97. [DOI: 10.1109/access.2020.3012740] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 1.3] [Reference Citation Analysis]
38 Zhao Y, Zhang W, Sun M, Liu X. An Improved Consensus Clustering Algorithm Based on Cell-Like P Systems With Multi-Catalysts. IEEE Access 2020;8:154502-17. [DOI: 10.1109/access.2020.3010475] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 1.3] [Reference Citation Analysis]
39 Soufiane K, Imene H, Manel A, Tarek KM. Clustering Ensemble Approach Based on Incremental Learning. Proceedings of the 9th International Conference on Information Systems and Technologies 2019. [DOI: 10.1145/3361570.3361603] [Reference Citation Analysis]
40 Mojarad M, Nejatian S, Parvin H, Mohammadpoor M. A fuzzy clustering ensemble based on cluster clustering and iterative Fusion of base clusters. Appl Intell 2019;49:2567-81. [DOI: 10.1007/s10489-018-01397-x] [Cited by in Crossref: 44] [Cited by in F6Publishing: 32] [Article Influence: 11.0] [Reference Citation Analysis]
41 Liang W, Zhang Y, Xu J, Lin D. Optimization of Basic Clustering for Ensemble Clustering: An Information-Theoretic Perspective. IEEE Access 2019;7:179048-62. [DOI: 10.1109/access.2019.2950159] [Cited by in Crossref: 5] [Cited by in F6Publishing: 5] [Article Influence: 1.3] [Reference Citation Analysis]
42 Wang Z, He D, Li B. Clustering of Copper Flotation Process Based on the AP-GMM Algorithm. IEEE Access 2019;7:160650-9. [DOI: 10.1109/access.2019.2951444] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 1.0] [Reference Citation Analysis]
43 Abbasi S, Nejatian S, Parvin H, Rezaie V, Bagherifard K. Clustering ensemble selection considering quality and diversity. Artif Intell Rev 2019;52:1311-40. [DOI: 10.1007/s10462-018-9642-2] [Cited by in Crossref: 42] [Cited by in F6Publishing: 45] [Article Influence: 8.4] [Reference Citation Analysis]