王河山
讲师、硕士生导师

电子邮箱:
whs**[at]163.com(请将[at]换成@)

办公室:
郑州大学电气工程学院1215

研究方向:
人工智能、动态神经网络、建模与优化、图像识别

教育背景
2011/09-2016/01，华东理工大学，信息工程学院，博士
2005/09-2009/06，郑州大学，电气工程学院，学士

工作经历
? 2016/01-至今，郑州大学，电气工程学院，直聘副教授
? 2018.12-2019.12，加拿大温莎大学，访问****

科研项目
? （主持）国家自然科学基金项目（**），2017.01-2019.12

代表文章
[1] Wang Heshan, Ni Chunjuan, Yan Xuefeng. Optimizing the echo state network based on mutual information for modeling fed-batch bioprocesses[J]. Neurocomputing, 2017, 225: 111-118.
[2] Wang H, Wu Q M J, Wang J, et al. Optimizing simple deterministically constructed cycle reservoir network with a Redundant Unit Pruning Auto-Encoder algorithm[J]. Neurocomputing , 2019, 356: 184-194.
[3] Wang H, Wu Q M J, Xin J, et al. Optimizing Deep Belief Echo State Network with a Sensitivity Analysis Input Scaling Auto-Encoder algorithm[J]. Knowledge-Based Systems, 2020, 191:5.
[4] Heshan Wang, Xuefeng Yan*. Reservoir Computing with Sensitivity Analysis Input Scaling Regulation and Redundant Unit Pruning for Modeling Fed-Batch Bioprocesses[J]. INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, 2014, 53(16):6789-6797.
[5] Heshan Wang, Xuefeng Yan*, Improved Simple Deterministically Constructed Cycle ReservoirNetwork with Sensitive Iterative Pruning Algorithm[J]. Neurocomputing, 2014, 145(18):353–362.
[6] Heshan Wang, Xuefeng Yan*.Optimizing the echo state network with a binary particle swarm optimization algorithm[J]. knowledge based systems, 2015, 86:182-193.
[7] Heshan Wang, Xuefeng Yan*. Chlorophyll-A Predicting Model Based On Dynamic Neural Network[J]. Applied Artificial Intelligence, 2015, 29(10): 962-978.