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Academic Journal of Mathematical Sciences, 2024, 5(3); doi: 10.25236/AJMS.2024.050301.

Analysis of the Research Status of SMOTE Algorithm in the Last Three Years—Statistical Analysis of Core Literature Based on CNKI 2022-2024


Guiyu Ou

Corresponding Author:
Guiyu Ou

College of Mathematics and Statistics, Sichuan University of Science and Engineering, Zigong, China


To clearly understand the research and application status of the SMOTE algorithm in China, In this paper, bibliometrics is used to study the core papers of the SMOTE algorithm published in CNKI in the last three years. This method takes the literature in the CNKI database from 2022 to 2024 as the retrieval object, and statistically analyzes the number of articles published by SMOTE algorithm in China, main authors, institutions, core journals, highly cited documents, research hotspots, and so on. The research status and hot spots in the last three years have been found. The research results provide a direction for the later research and application of the SMOTE algorithm.


SMOTE algorithm; Bibliometric method; Algorithm improvement; Research on algorithm application

Cite This Paper

Guiyu Ou. Analysis of the Research Status of SMOTE Algorithm in the Last Three Years—Statistical Analysis of Core Literature Based on CNKI 2022-2024. Academic Journal of Mathematical Sciences (2024) Vol. 5, Issue 3: 1-7. https://doi.org/10.25236/AJMS.2024.050301.


[1] Ma He, Song Mei, Zhu Yi. borderline-SMOTE oversampling method with improved boundary classification[J]. Journal of Nanjing University (Natural Science), 2023, 59(06): 1004-1006. 

[2] Li Ang, Han Meng, Mu Dongliang, Gao Zhihui, Liu Shujuan. summary of classification methods of multi-class unbalanced data[J]. application research of computers, 2022, 39(12): 3535-3536. 

[3] Haixiang Lin, Zhao Zhengxiang, Lu Renjie, Lu Ran, Bai Wansheng, Hu Nana. multi-level fault diagnosis combined model of high-speed rail turnout based on word fusion[J]. journal of electronic measurement and instrument, 2022, 36(10): 217-226. 

[4] Haixiang Lin, Lu Ran, Lu Renjie, Li Xinqin, Zhao Zhengxiang, Bai Wansheng. Fault diagnosis of high-speed rail vehicle-mounted equipment based on BiLSTM-CBA combined model[J]. china safety science journal, 2022, 32(06): 79-86. 

[5] Haixiang Lin, Lu Renjie, Lu Ran, Xu Li. Automatic fault classification method of railway signal equipment based on text mining[J]. Journal of Yunnan University (Natural Science Edition), 2022, 44(02): 281-289. 

[6] Wang Lichun, Liu Shuisheng. Research on Improved Random Forest Algorithm Based on Mixed Sampling and Feature Selection[J]. Journal of Nanjing University of Posts and Telecommunications (Natural Science Edition), 2022, 42(01): 81-89. 

[7] Luo Chaoyueling, Zheng Yunxin, Xu Jiyu, Xie Yulong, Dai Mingcheng, Li Li. Improved GWO-SVM transformer fault diagnosis method based on Borderline-SMOTE-IHT mixed sampling[J]. Wisdom electric power, 2023, 51(07): 108-114. 

[8] Zhu Shen, Xu Hua, Cheng Jinhai. Resampling Algorithm for Unbalanced Data[J]. Journal of chinese computer systems, 2024, 45(03): 542-548. 

[9] Wang Li, Chen Jili, Xie Xiaolan, Xu Rongan. Neural Network Classification Model Based on Chaotic Tianniu Algorithm Optimization[J]. Science technology and engineering, 2022, 22(12): 4854-4863. 

[10] Li Ruiping, Zhu Junjie. prediction of coronary heart disease based on improved Borderline-Smote-GBDT[J]. Chinese journal of medical physics, 2023, 40(10): 1278-1284. 

[11] Sheng Jianlong, Qiao Yu, Wang Ping, Yu Donghua, Zhang Yanwen. Study on risk prediction of mine karst collapse under the influence of groundwater based on LOF-SMOTE algorithm[J]. nonferrous metal science and engineering, 2023, 14(03): 372-380. 

[12] Zhou Zhihao, Chen Lei, Wu Xiang, Qiu Dongliang, Liang Guangsheng, Zeng Fanqiao. intrusion detection algorithm of vehicle-mounted CAN bus based on SMOTE-SDSAE-SVM[J]. computer science, 2022, 49(s1): 562-570.