头像
Zhongyiwen
Professor
Center of Modern Education Technology and Information Management
Post:
Dean
Title:
Professor
Degree:
Ph.D
Tel:
0591-83509681
Email:
yiwzhong AT fafu.edu.cn
Office:
A312, JinShan Building
Address:
A312, JinShan Building, Fujian Agriculture and Forestry University
PostCode:
350002

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  • I am Professor at the College of Computer and Information at the Fujian Agriculture and Forestry University, Fuzhou, China. I received PhD in Computer Science and Technology from Zhejiang University in 2005. My current research interests include computational intelligence, data visualisation and bioinformatics.


  • Education Experiences

    1985-1989: East China Normal University, Bachelor in Physics

    1999-2002: Zhejiang University, Master in Computer Science and Technology

    2002-2005: Zhejiang University, Ph.D. in Computer Science and Technology 


  • Work Experiences

    2008.11-present: Professor, Computer Science and Technology, Fujian Agriculture and Forestry University

    2011.4-2012.6: Visiting Scholar, Computational Cognition and Learning Laboratory, Indiana University

    2007.10-2008.4: Visiting Scholar, Computational Cognition and Learning Laboratory, Indiana University

    2002.8-2008.10: Associate Professor, Computer Science and Technology, Fujian Agriculture and Forestry University

    1995.8-2002.7: Lecturer, Computer Science and Technology, Fujian Agriculture and Forestry University

    1989.9-1995.7: Assistant, Physics, Fujian Agriculture and Forestry University


    • Research Fields

    Computational Intelligence

    Machine Learning


    Teachings

    Java Programming


    Machine Learning and Intelligent Computation

    Data Mining


    Projects


    Study of List-based Adaptive Simulated Annealing Algorithm and Its Parallelization. Special Fund for Scienti c and Technological Innovation of Fujian Agriculture and Forestry University (CXZX2016026). 2017-2019. Principal Investigator

    Study of key technologies for allpications of big data in Agriculture and Foretry fields. Special Fund for Scienti c and Technological Innovation of Fujian Agriculture and Forestry University (CXZX2016031). 2017-2019. Principal Investigator

    Study of Population-Based learnable Simulated Annealing Algorithm and its Application, principal Investigator, Natural Science Foundation of FuJian Province (2013J01216)

    Study of Particle Swarm Optimization Based on Machine Learning, principal Investigator, Natural Science Foundation of FuJian Province (2008J0316)

    Study of the Nature-inspired Computing Model Based on Population, principal Investigator, FuJian Provincial Innovation Foundation for Young Science and Technology Talents (2006F3013)

    Study of Particle Swarm Optimization Algorithm and Its Application, co-investigator, Natural Science Foundation of FuJian Province (2006J0018)

      


    Publications

    Zhan, S., Wang, L., Zhang, Z., Zhong Y.( Corresponding). Noising methods with hybrid greedy repair operator for 0–1 knapsack problem, Memetic Comp. (2019). https://doi.org/10.1007/s12293-019-00288-z

    Yiwen Zhong, Lijin Wang, Min Lin, Hui Zhang, Discrete pigeon-inspired optimization algorithm with Metropolis acceptance criterion for large-scale traveling salesman problem, Swarm and Evolutionary Computation, 2019, https://doi.org/10.1016/j.swevo.2019.04.002.

    S. Zhan, Z. Zhang, L. Wang and Y. Zhong (Corresponding), List-based Simulated Annealing Algorithm with Hybrid Greedy Repair and Optimization Operator for 0-1 Knapsack Problem, in IEEE Access. doi: 10.1109/ACCESS.2018.2872533

    Zhong Y, Lin J, Wang L, et al. Discrete comprehensive learning particle swarm optimization algorithm with Metropolis acceptance criterion for traveling salesman problem[J]. Swarm and evolutionary computation, 2018: 77-88.

    Lin Juan, Zhong Yiwen, Li Erna, et al. Multi-Agent Simulated Annealing Algorithm with Parallel Adaptive Multiple Sampling for Protein Structure Prediction in AB off-lattice model[J]. Applied Soft Computing, 2018, 62: 491-503.

    Zhong Y, Lin J, Wang L, et al. Hybrid Discrete Artificial Bee Colony Algorithm with Threshold Acceptance Criterion for Traveling Salesman Problem[J]. Information Sciences, 2017, 421: 70-84.

    Zhan, Shihua, et al. Comparative analysis of selection schemes used in artificial bee colony algorithm. International Journal of Computing Science and Mathematics 8.3 (2017): 218-227. (Corresponding)

    Wang L, Zhong Y, Yin Y. Nearest neighbour cuckoo search algorithm with probabilistic mutation[J]. Applied Soft Computing, 2016, 49: 498-509.

    Zhan, Shi-hua, et al. List-based simulated annealing algorithm for traveling salesman problem. Computational intelligence and neuroscience 2016 (2016): 8. (Corresponding) http://jszy.fafu.edu.cn/_ueditor/themes/default/images/icon_pdf.gifList-Based Simulated Annealing Algorithm for Traveling Salesman Problem.pdf

    Wang, C., Lin, M., Zhong, Y. (Corresponding), & Zhang, H. Swarm simulated annealing algorithm with knowledge-based sampling for travelling salesman problem. International Journal of Intelligent Systems Technologies and Applications 15.1 (2016): 74-94.

    Wang, C., Lin, J., Lin, M., & Zhong, Y. (Corresponding). Evolutionary harmony search algorithm with Metropolis acceptance criterion for travelling salesman problem. International Journal of Wireless and Mobile Computing, 2016, 10(2), 166-173.

    Yiwen Zhong, Juan Lin, Qingliang Du, Limei Wang. Multi-agent simulated annealing algorithm based on differential perturbation for protein structure prediction problems. Int. J. of Computer Applications in Technology[J], 2015 Vol.51, No.3, pp.164 - 172

    Yiwen Zhong, Juan Lin, Hui Yang, Hui Zhang. Analysis of learning–based multi–agent simulated annealing algorithm for function optimisation problems[J]. International Journal of Computing Science and Mathematics, 4(4): 382-391, 2013.

    Juan Lin, Jing Ning, Qingliang Du, and Yiwen Zhong (Corresponding author). Multi-agent Simulated Annealing Algorithm Based on Particle Swarm Optimization Algorithm for Protein Structure Prediction. Journal of Bionanoscience, 7(1), 84-91, 2013.

    Lijin Wang and Yiwen Zhong (Corresponding author). A modified group search optimizer for constrained optimization problems. Int. J. Modelling, Identification and Control. 18(3):276-283, 2013.

    Xiaoyu Lin, Yiwen Zhong (Corresponding author), and Hui Zhang. An enhanced firefly algorithm for function optimisation problems. Int. J. Modelling, Identification and Control. 18(2):166-172, 2013.

    王李进, 尹义龙, 钟一文. 逐维改进的布谷鸟搜索算法. 软件学报. 24(11):2687-2698, 2013.

    Yiwen Zhong, Lijin Wang, Changying Wang, and Hui Zhang. Multi-agent Simulated Annealing Algorithm Based on Differential Evolution Algorithm, International Journal of Bio-Inspired Computation,4(4), 217-228, 2012.

    Yiwen Zhong, Jing Ning, Hui Zhang. Multi-agent Simulated Annealing Algorithm Based on Particle Swarm Optimization Algorithm, International Journal of Computer Applications in Technology, 43(4), 335-342, 2012.

    Yiwen Zhong, Xian Liu, Lijin Wang, and Changying Wang. Particle Swarm Optimization Algorithm with Iterative Improvement Strategy for Multi-dimensional Function Optimization Problems, International Journal of Innovative Computing and Applications, 4(3/4), 223-232, 2012.

      


    Achievements