OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Active Sample Selection Based Incremental Algorithm for Attribute Reduction With Rough Sets
Yanyan Yang, Degang Chen, Hui Wang
IEEE Transactions on Fuzzy Systems (2016) Vol. 25, Iss. 4, pp. 825-838
Open Access | Times Cited: 88

Showing 1-25 of 88 citing articles:

Feature Selection Based on Neighborhood Self-Information
Changzhong Wang, Yang Huang, Mingwen Shao, et al.
IEEE Transactions on Cybernetics (2019) Vol. 50, Iss. 9, pp. 4031-4042
Closed Access | Times Cited: 216

Multi-source information fusion based on rough set theory: A review
Pengfei Zhang, Tianrui Li, Guoqiang Wang, et al.
Information Fusion (2020) Vol. 68, pp. 85-117
Closed Access | Times Cited: 214

Fuzzy rough set-based attribute reduction using distance measures
Changzhong Wang, Yang Huang, Mingwen Shao, et al.
Knowledge-Based Systems (2018) Vol. 164, pp. 205-212
Closed Access | Times Cited: 208

GBNRS: A Novel Rough Set Algorithm for Fast Adaptive Attribute Reduction in Classification
Shuyin Xia, Hao Zhang, Wenhua Li, et al.
IEEE Transactions on Knowledge and Data Engineering (2020) Vol. 34, Iss. 3, pp. 1231-1242
Closed Access | Times Cited: 160

Attribute reduction with fuzzy rough self-information measures
Changzhong Wang, Yang Huang, Weiping Ding, et al.
Information Sciences (2020) Vol. 549, pp. 68-86
Closed Access | Times Cited: 146

Attribute reduction based on k-nearest neighborhood rough sets
Changzhong Wang, Yunpeng Shi, Xiaodong Fan, et al.
International Journal of Approximate Reasoning (2018) Vol. 106, pp. 18-31
Open Access | Times Cited: 160

Attribute reduction for multi-label learning with fuzzy rough set
Yaojin Lin, Yuwen Li, Chenxi Wang, et al.
Knowledge-Based Systems (2018) Vol. 152, pp. 51-61
Closed Access | Times Cited: 132

Active Incremental Feature Selection Using a Fuzzy-Rough-Set-Based Information Entropy
Xiao Zhang, Changlin Mei, Degang Chen, et al.
IEEE Transactions on Fuzzy Systems (2019) Vol. 28, Iss. 5, pp. 901-915
Closed Access | Times Cited: 124

Incremental Perspective for Feature Selection Based on Fuzzy Rough Sets
Yanyan Yang, Degang Chen, Hui Wang, et al.
IEEE Transactions on Fuzzy Systems (2017) Vol. 26, Iss. 3, pp. 1257-1273
Open Access | Times Cited: 112

Rebooting data-driven soft-sensors in process industries: A review of kernel methods
Yiqi Liu, Min Xie
Journal of Process Control (2020) Vol. 89, pp. 58-73
Closed Access | Times Cited: 108

Online Active Learning in Data Stream Regression Using Uncertainty Sampling Based on Evolving Generalized Fuzzy Models
Edwin Lughofer, Mahardhika Pratama
IEEE Transactions on Fuzzy Systems (2017) Vol. 26, Iss. 1, pp. 292-309
Closed Access | Times Cited: 91

Incremental Feature Selection Using a Conditional Entropy Based on Fuzzy Dominance Neighborhood Rough Sets
Binbin Sang, Hongmei Chen, Lei Yang, et al.
IEEE Transactions on Fuzzy Systems (2021) Vol. 30, Iss. 6, pp. 1683-1697
Closed Access | Times Cited: 91

A Deep Learning Model for Concrete Dam Deformation Prediction Based on RS-LSTM
Xudong Qu, Jie Yang, Meng Chang
Journal of Sensors (2019) Vol. 2019, pp. 1-14
Open Access | Times Cited: 72

A fuzzy rough set-based feature selection method using representative instances
Xiao Zhang, Changlin Mei, Degang Chen, et al.
Knowledge-Based Systems (2018) Vol. 151, pp. 216-229
Closed Access | Times Cited: 66

Feature selection for multi-label learning based on kernelized fuzzy rough sets
Yuwen Li, Yaojin Lin, Jinghua Liu, et al.
Neurocomputing (2018) Vol. 318, pp. 271-286
Closed Access | Times Cited: 65

Feature selection for dynamic interval-valued ordered data based on fuzzy dominance neighborhood rough set
Binbin Sang, Hongmei Chen, Lei Yang, et al.
Knowledge-Based Systems (2021) Vol. 227, pp. 107223-107223
Closed Access | Times Cited: 53

Incremental feature selection by sample selection and feature-based accelerator
Yanyan Yang, Degang Chen, Xiao Zhang, et al.
Applied Soft Computing (2022) Vol. 121, pp. 108800-108800
Closed Access | Times Cited: 29

A novel covering rough set model based on granular-ball computing for data with label noise
Xiaoli Peng, Yuanlin Gong, Xianghui Hou, et al.
International Journal of Approximate Reasoning (2025), pp. 109420-109420
Closed Access

Feature selection based on maximal neighborhood discernibility
Changzhong Wang, Qiang He, Mingwen Shao, et al.
International Journal of Machine Learning and Cybernetics (2017) Vol. 9, Iss. 11, pp. 1929-1940
Closed Access | Times Cited: 58

Incremental approaches for heterogeneous feature selection in dynamic ordered data
Binbin Sang, Hongmei Chen, Tianrui Li, et al.
Information Sciences (2020) Vol. 541, pp. 475-501
Closed Access | Times Cited: 40

A Novel Feature Selection Method for High-Dimensional Mixed Decision Tables
Nguyễn Ngọc Thủy, Sartra Wongthanavasu
IEEE Transactions on Neural Networks and Learning Systems (2021) Vol. 33, Iss. 7, pp. 3024-3037
Closed Access | Times Cited: 39

A Novel Multi-Criteria Decision-Making Method Based on Rough Sets and Fuzzy Measures
Jingqian Wang, Xiaohong Zhang
Axioms (2022) Vol. 11, Iss. 6, pp. 275-275
Open Access | Times Cited: 26

Incremental rough reduction with stable attribute group
Xin Yang, Miaomiao Li, Hamido Fujita, et al.
Information Sciences (2022) Vol. 589, pp. 283-299
Closed Access | Times Cited: 25

A two-way accelerator for feature selection using a monotonic fuzzy conditional entropy
Yanyan Yang, Degang Chen, Zhenyan Ji, et al.
Fuzzy Sets and Systems (2024) Vol. 483, pp. 108916-108916
Closed Access | Times Cited: 5

Rough set Theory-Based group incremental approach to feature selection
Jie Zhao, Daiyang Wu, Yongxin Zhou, et al.
Information Sciences (2024) Vol. 675, pp. 120733-120733
Closed Access | Times Cited: 4

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