Personal Information

Lecturer (higher education)


Date of Birth:1991-08-16

Education Level:博士研究生

Degree:Doctoral Degree in Philosophy



Administrative Position:教师


范宗文 华侨大学计算机科学与技术学院讲师。主要研究方向为:机器学习,模糊系统,数据挖掘。


(1) 2017-09 至 2021-08, 澳大利亚纽卡斯尔大学, 计算机科学, 博士

(2) 2014-09 至 2017-06, 华侨大学, 计算机技术, 硕士

(3) 2010-09 至 2014-07, 华侨大学, 软件工程, 学士





(1) 机器学习相关算法的改进

(2) 深度模糊系统研究


[1] Zongwen Fan, Raymond Chiong, and Fabian Chiong. A fuzzy-weighted Gaussian kernel-based machine learning approach for body fat prediction [J]. Applied Intelligence, 2022, 52: 2359-2368. 

[2] Zongwen Fan, Raymond Chiong, Zhongyi Hu, and Yuqing Lin. A fuzzy weighted relative error support vector machine for reverse prediction of concrete components [J]. Computers and Structures, 2020, 230, 106171. 

[3] Zongwen Fan, Raymond Chiong, Zhongyi Hu, and Yuqing Lin. A multi-layer fuzzy model based on fuzzy-rule clustering for prediction tasks [J]. Neurocomputing, 2020, 410, 114-124.

[4] Zongwen Fan, Raymond Chiong, Zhongyi Hu, Sandeep Dhakal, and Yuqing Lin. A two-layer Wang-Mendel fuzzy approach for predicting the residuary resistance of sailing yachts [J]. Journal of Intelligence & Fuzzy Systems, 2019, 36(6): 6219-6229. 

[5] Zongwen Fan, Jin Gou, Cheng Wang, Wei Luo. Fuzzy model identification based on fuzzy-rule clustering and its application for airfoil noise prediction [J]. Journal of Intelligent & Fuzzy Systems, 2017, 33(3): 1603-1611. 

[6] Raymond Chiong, Zuli Wang, Zongwen Fan, and Sandeep Dhakal. A fuzzy-based ensemble model for improving malicious web domain identification. Expert Systems with Applications, 2022, 204: 117243.

[7] Jin Gou, Zongwen Fan, Cheng Wang, Wei Luo and Haixiao Chi. An improved Wang-Mendel method based on the FSFDP clustering algorithm and sample correlation. Journal of Intelligent & Fuzzy Systems, 2016, 31(6):2839-2850.

[8] Zongwen Fan, Fenlin Wu, and Yaxuan Tang. A hierarchy-based machine learning model for happiness prediction. Applied Intelligence, 2023, 53:7108–7117.

[9] Wenjie Yin, Zongwen Fan*, Natthachet Tangdamrongsub, Litang Hu, Menglin Zhang. Comparison of physical and data-driven models to forecast groundwater level changes with the inclusion of GRACE - A case study over the state of Victoria, Australia [J], Journal of Hydrology, 2021, 602: 126735.

[10] Raymond Chiong, Zongwen Fan*, Zhongyi Hu, and Sandeep Dhakal. A novel ensemble learning approach for stock market prediction based on sentiment analysis and the sliding window method. IEEE Transactions on Computational Social Systems, 2022, doi: 10.1109/TCSS.2022.3182375.

[11] Shaleeza Sohail, Zongwen Fan*, Xin Gu, and Fariza Sabrina. Multi-tiered Artificial Neural Networks model for intrusion detection in smart homes. Intelligent Systems with Applications, 2022, 16: 200152.

[12] Weinan Li, Jin Gou, and Zongwen Fan. Session-based recommendation with temporal convolutional network to balance numerical gaps. Neurocomputing, 2022, 493: 166-175.

[13] Zongwen Fan, and Jin Gou. Predicting body fat using a novel fuzzy-weighted approach optimized by the whale optimization algorithm. Expert Systems with Applications, 2023, 217: 119558

[14] Zongwen Fan, and Raymond Chiong. Identifying digital capabilities in university courses: An automated machine learning approach. Education and Information Technologies, 2022, doi: 10.1007/s10639-022-11075-8.

[15] Raymond Chiong, Zongwen Fan, Zhongyi Hu, and Fabian Chiong. Using an improved relative error support vector machine for body fat prediction [J]. Computer Methods and Programs in Biomedicine, 2021, 198: 105749. 

[16] Jin Gou, Zongwen Fan, Cheng Wang, Wangping Guo, Xiongming Lai, Meizhen Chen. A minimum-of-maximum relative error support vector machine for simultaneous reverse prediction of concrete components [J]. Computers & Structures, 2016, 172: 59-70. 

[17] Mingzhe Li, HongBo Zhang, Qing Lei, Zongwen Fan, Jinghua Liu, and JiXiang Du. Pairwise contrastive learning network for action quality assessment. In the 17th European Conference Computer Vision–ECCV, 2022, pp. 457-473.

[18] Raymond Chiong, Zongwen Fan, Zhongyi Hu, Marc TP Adam, Bernhard Lutz, and Dirk Neumann. A sentiment analysis-based machine learning approach for financial market prediction via news disclosures. In Proceedings of the Genetic and Evolutionary Computation Conference Companion–GECCO, 2018, 278-279.



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