一、基本信息
姓 名：马云鹏
职 称：讲 师
学科专业：计算机科学与技术
通讯地址：天津商业大学信息工程学院
电子信箱：mayunpeng@tjcu.edu.cn
二、研究方向
机器学习，仿生智能计算，复杂过程控制优化；主要应用领域为特征提取、复杂系统动态建模和参数整定等。
三、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, 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.
[3] 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.
[4] 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.
[5] 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.
[6] 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.
[7] 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.
[8] 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.
[9] 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.
[10] 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.
[11] 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.
[12] 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.
[13] 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.
[14] 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.
[15] 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.
四、科研项目
1 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.
2 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.
3 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.
4 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.
5 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.
6 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.
