马云鹏，男，工学博士，副教授，学院副院长，硕士生导师

电子信箱：mayunpeng@tjcu.edu.cn

主要教育及工作经历

（1）2022.12至今：天津商业大学信息工程学院，副教授，硕士生导师；

（2）2018.07-2022.12：天津商业大学信息工程学院，讲师，硕士生导师；

（3）2014.09-2018.06：燕山大学电气工程学院自动化系，控制科学与工程专业，研究生，获工学博士学位；

（4）2012.09-2014.08：燕山大学电气工程学院自动化系，控制理论与控制工程专业，研究生，硕博连读；

（5）2008.09-2012.07：燕山大学里仁学院电气工程学院，自动化专业，获工学学士学位。

研究方向

 信号与信息处理方向，主要包括：

（1）机器学习及应用

（2）智能计算与信息处理

获得荣誉

2021年评为“五比双创”青年示范岗优秀个人。

2023年评为校级优秀共产党员。

代表性论著

[1] Ma Yunpeng , Zhang Xinxin* , Song Jiancai , Chen Lei. A modified teaching–learning-based optimization algorithm for solving optimization problem[J]. Knowledge-Based Systems, 2021, 212:106599.

[2] Ma Yunpeng, Xu Chenheng, Wang Hua, Liu Shengkai, Gu Xiaoying. Time series online forecasting based on Sequence Decomposition Learning Networks[J].Applied Soft Computing, 2023, 148:110907.

[3] Ma Yunpeng, Xu Chenheng*, Wang Hua, Wang Ran, Liu Shilin, Gu Xiaoying. Model NOx, SO2 Emissions Concentration and Thermal Efficiency of CFBB Based on a Hyper-Parameter Self-Optimized Broad Learning System[J]. Energies, 2022, 15:7700.

[4] Ma Yunpeng, Chang Chang, Lin Zehua, Zhang Xinxin, Song Jiancai, Chen Lei. Modified Marine Predators Algorithm hybridized with teaching learning mechanism for solving optimization problems[J].Mathematical Biosciences and Engineering, 2022, 20(1): 93–127.

[5] Ma Yunpeng, Wang Heqi, Zhang Xinxin, et al. Three-objective optimization of boiler combustion process based on multi-objective teaching-learning based optimization algorithm and ameliorated extreme learning machine[J]. Machine Learning with Applications, 2021, 5:100082.

[6] Ma Yunpeng, Niu Peifeng*, Yan Shanshan, Li Guoqiang. A modified online sequential extreme learning machine for building circulation fluidized bed boiler's NOx emission model[J]. Applied mathematics and computation. 2018, 334:214-226. 

[7] Ma Yunpeng, Niu Peifeng*, Zhang Xinxin, Li Guoqiang. Research and application of quantum-inspired double parallel feed-forward neural network[J]. Knowledge-Based Systems, 2017, 136:140-149.

[8] Niu Peifeng, Ma Yunpeng*, Yan Shanshan. A modified teaching-learning-based optimization algorithm for numerical function optimization[J]. International Journal of Machine Learning and Cybernetics, 2019,10:1357-1371.

[9] Niu Peifeng, Ma Yunpeng*, Li Guoqiang. Model NOx emission and thermal efficiency of CFBB based on an ameliorated extreme learning machine[J]. Soft computing, 2018, 22:4685-4701.

[10] Niu Peifeng, Ma Yunpeng*, Li Mengning, Yan Shanshan, Li Guoqiang. A Kind of Parameters Self-adjusting Extreme Learning Machine[J]. Neural Processing Letters, 2016, 44(3):813-830. 

[11] Zhang Xinxin , Ma Yunpeng* . LMIs conditions to robust pinning synchronization of uncertain fractional-order neural networks with discontinuous activations[J]. Soft Computing, 2020, 24(21):15927-15935.

[12] Song Jiancai, Zhang Liyi, Jiang Qingling, Ma Yunpeng, et al. Estimate the daily consumption of natural gas in district heating system based on a hybrid seasonal decomposition and temporal convolutional network model[J]. Applied Energy, 2022, 309:118444.

[13] Song Jiancai, Zhang Liyi, Xue Guixiang, Ma Yunpeng, et al. Predicting Hourly Heating Load in a District Heating System Based on a Hybrid CNN-LSTM Model[J]. Energy and Buildings, 2021, 243（3）:110998.

[14] Yu Bai, Pan Xuhua, Li Xuefeng, Liu Gaohua, Ma Yunpeng*. Object Detection Algorithm Based on Improved Feature Pyramid[J]. Scientific programming, 2022:3583399.

[15] Chen Lei, Hao Congwang, Ma Yunpeng. A Multi-Disturbance Marine Predator Algorithm Based on Oppositional Learning and Compound Mutation[J]. Electronics, 2023, 11(24):4087.

[16] Chen Lei, Song Na, Ma Yunpeng. Harris hawks optimization based on global cross-variation and tent mapping[J]. Journal of supercomputing, 2023, 79(5):5576-5614.

[17] Zhang Xinxin, Ma Yunpeng, Gao Shan, Song Jiancai, Chen Lei. Robust synchronization analysis of delayed fractional order neural networks with uncertain parameters[J]. AIMS MATHEMATICS, 2022, 7(10):18883-18896.

[18] Chen Lei, Tian Yu, Ma Yunpeng. An improved grasshopper optimization algorithm based on dynamic dual elite learning and sinusoidal mutation[J]. Computing, 2022, 104(5):981-1015.

[19] Song Jiancai, Xue Guixiang, Pan Xuhua, Ma Yunpeng, Li Han. Hourly Heat Load Prediction Model Based on Temporal Convolutional Neural Network[J]. IEEE ACCESS, 2020, 8:16726-16741.

[20] Chen Lei, Feng Changzhou, Ma Yunpeng. Improved Harris Hawks optimization for global optimization and engineering design[J]. 2023.

[21] Liu Shilin, Ma Yunpeng, Wang Ran, Dong Wenju, Wang Yuyin. Optimize the NOx emission concentration of Circulation Fluidized Bed Boiler based on on-line learning neural network and modified TLBO algorithm[C]. ICMLC 2022: 2022 14th International Conference on Machine Learning and Computing (ICMLC), 2022.   (EI)

[22] Ma Yunpeng, Tang Haoheng, Wang Heqi, Wang Zhenying, Zhang Xinxin, Li Lipeng. A novel chaotic teaching learning based optimization algorithm and its application in optimization of extreme learning machine[C]. Journal of physics:conference series, 2021.

[23] Zhang Xinxin , Niu Peifeng , Hu Xiaobin , Ma Yunpeng, Li Guoqiang. Global quasi-synchronization and global anti-synchronization of delayed neural networks with discontinuous activations via non-fragile control strategy[J]. Neurocomputing, 2019, 361(7):1-9.

[24] Zhang Xinxin, Niu Peifeng*, Ma Yunpeng, Wei Yanqiao, Li Guoqiang. Global Mittag-Leffler stability analysis of fractional-order impulsive neural networks with one-side Lipschitz condition[J]. Neural networks : the official journal of the International Neural Network Society, 2017, 94:67.

[25] Niu Peifeng, Chen Ke*, Ma Yunpeng, Li Xia, Liu Aling, Li Guoqiang. Model turbine heat rate by fast learning network with tuning based on ameliorated krill herd algorithm[J]. Knowledge-Based Systems, 2016, 118(15):80-92.

[26] Li Guoqiang, Niu Peifeng, Ma Yunpeng, Wang Hongbin, Zhang Weiping. Tuning extreme learning machine by an improved artificial bee colony to model and optimize the boiler efficiency[J]. Knowledge-Based Systems, 2014, 67(3):278-289.

[27] 马云鹏，牛培峰, 陈科, 闫姗姗, 李国强. 基于混沌分组教与学优化算法锅炉NO x模型优化研究[J]. 计量学报, 2018, 39(1):125-129. 

[28] 牛培峰, 马云鹏*, 张京, 张鑫, 李国强. 基于相关向量机的电站锅炉NOx燃烧优化[J]. 计量学报, 2016, 37(2):191-196.

[29] 牛培峰, 马云鹏*, 张欣欣,胡晓宾. 基于人工智能技术的火电厂燃煤锅炉智能燃烧优化研究及应用[J]. 智能科学与技术学报, 2019, 1(2):143-170.

[30] 牛培峰, 吴志良, 马云鹏, 史春见, 李进柏. 基于鲸鱼优化算法的汽轮机热耗率模型预测[J]. 化工学报, 2017, 68(3):1049-1057.

 

科研项目

[1] 主持. 基于知识和数据双驱动的锅炉燃烧系统多目标优化策略研究（62203332），国家自然科学基金青年项目，2022.

[2] 主持. 循环流化床锅炉燃烧过程系统建模与参数整定研究（20JCQNJC00430）,天津市自然科学基金青年项目, 2020年.

[3] 参与. 基于区块链的物联网采集终端的设计与系统实现, 天津市科技特派员项目, 2020.

[4] 参与. 基于人工智能的集中供热负荷预测与动态调控关键技术研究, 天津市科技特派员项目, 2019.

[5] 参与. 基于样本增量驱动的量子快速学习网络模型与蜂群算法研究及其在循环流化床锅炉燃烧过程优化控制中的应用（61573306），国家自然科学基金资助项目，2016.

[6] 参与. 新型神经网络算法研究及其在锅炉燃烧优化中的应用（61403331），国家自然科学基金资助项目，2015.

[7] 参与. 基于人工智能的煤粉炉燃烧过程系统建模与参数整定（BJ2017033），河北省高等学校青年拔尖人才资助项目，2017.

[8] 参与. 具有不确定参数的时滞分数阶神经网络的鲁棒准同步控制，天津市高校科技发展基金项目，2022.

[9] 参与. 面向CPS的高效状态感知方法研究，天津市高校科技发展基金项目，2022.

获奖成果

[1] 获全国大学生数学建模竞赛2021，天津赛区一等奖，唯一指导教师。

[2] 获第七届全国大学生统计建模大赛全国一等奖，第一指导教师。

发明专利

谷晓英; 赵春海; 韩建枫; 马云鹏; 吴玉霄. 一种非集中递归式动态负载均衡计算架构. 授权发明专利号：CN202110382691.6