贺彦林(Yan-Lin He)：副教授，硕士生导师；
2016年6月北京化工大学控制科学与工程博士毕业，当年以北京化工大学“青年后备引进人才”留校在自动化系任教；2019年担任自动化系系主任，当年入选北京化工大学“青年英才”。现任中国自动化学会应用专委会委员、中国自动化学会数据驱动控制、学习与优化专业委员会委员、中国自动化学会会员、北京自动化学会会员等。近五年，以第一作者/通信作者在IEEE T CONTR SYST T、CES、IECR、JPC、ISA T、CHEMOLAB、EAAI、Applied Energy、化工学报等期刊和国内外会议发表SCI/EI论文近60篇，获批专利2项，申请专利11项；目前主持国家自然科学基金青年项目，参与多项国家自然科学基金项目和中石化、中石油工程应用项目；获得北京市科协2020-2022年度青年人才托举计划和2018年北京自动化学会“青年科技创新人才”奖等。
研究方向：人工智能、系统建模与优化、软测量、故障诊断、数据挖掘、机器学习等。

教学课程Teaching courses
课程名称
面向对象

人工智能及应用
本科生

自动化科学导论
本科生

智能制造系统
研究生

系统工程理论
研究生

故障检测与诊断技术
研究生


主持、参与的主要科研项目 Research Projects
项目名称
项目来源

基于VSG 及 ELM 的复杂石化过程智能建模方法研究
国家自然科学基金青年项目

复杂石化过程智能化建模与诊断
智能过程系统工程教育部工程研究中心基地创新项目

工控系统安全主动防御机制及体系
研究
国家重点研发计划项目

面向故障诊断的动态时间维度信息挖掘理论研究
自由探索项目

食品安全多源异构大数据融合技术
研究
智能过程系统工程教育部工程研究中心基地创新项目


代表论文Research Papers
He Y.L.; Zhao Y.; Hu X.; Yan X.N.; Zhu Q.X.; Xu Y. Fault diagnosis using novel AdaBoost based discriminant locality preserving projection with resamples. Engineering Applications of Artificial Intelligence. 2020, 103631.
Xu, Y., Fan, C., Zhu, Q. X., Rajabifard, A., Chen, N., Chen, Y., & He, Y. L^*. Novel Pattern Matching integrated KCVA with adaptive rank-order morphological filter and Its Application to Fault Diagnosis [J]. Industrial & Engineering Chemistry Research, 2020.
Wang J, He Y L*, Zhu Q X. Energy and production efficiency optimization of an ethylene plant considering process operation and structure[J]. Industrial & Engineering Chemistry Research, 2020.
Xu Y, Jiang H, Zhang W, Zhu Q X He Y L^*, & Zhu Q X. Prediction intervals based soft sensor development using fuzzy information granulation and an improved recurrent ELM[J]. Chemometrics and Intelligent Laboratory Systems, 2019, 195: 103877.
Zhu Q X, Luo Y, He Y L^*. Novel Distributed Alarm Visual Analysis Using Multicorrelation Block-Based PLS and Its Application to Online Root Cause Analysis[J]. Industrial & Engineering Chemistry Research, 2019, 58(45): 20655-20666.
He Y L, Yan X, Zhu Q X. Novel Pattern Recognition Using Bootstrap-Based Discriminant Locality-Preserving Projection and Its Application to Fault Diagnosis [J]. Industrial & Engineering Chemistry Research, 2019, 58(38): 17906-17917.
Zhu Q X, Luo Y, He Y L*. Novel Multiblock Transfer Entropy Based Bayesian Network and Its Application to Root Cause Analysis [J]. Industrial & Engineering Chemistry Research, 2019, 58(12): 4936-4945.
Meng Q Q, Zhu Q X, Gao H H, He Y L*, et al. A novel scoring function based on family transfer entropy for Bayesian networks learning and its application to industrial alarm systems [J]. Journal of Process Control, 2019, 76: 122-132.
Xu Y, Shen S Q, He Y L*, et al. A Novel Hybrid Method Integrating ICA-PCA With Relevant Vector Machine for Multivariate Process Monitoring [J]. IEEE Transactions on Control Systems Technology, 2018, 27(4): 1780-1787.
Zhu Q X, Zhang C, He Y L*, et al. Energy modeling and saving potential analysis using a novel extreme learning fuzzy logic network: A case study of ethylene industry [J]. Applied Energy, 2018, 213: 322-333.
Zhang X H, Zhu Q X, He Y L*, et al. Energy modeling using an effective latent variable based functional link learning machine [J]. Energy, 2018, 162: 883-891.
Zhang X H, Zhu Q X, He Y L*, et al. A novel robust ensemble model integrated extreme learning machine with multi-activation functions for energy modeling and analysis: Application to petrochemical industry [J]. Energy, 2018, 162: 593-602.
Xu Y, Zhang M, Ye L, Zhu Q X, Geng Z Q, He Y L*, et al. A novel prediction intervals method integrating an error & self-feedback extreme learning machine with particle swarm optimization for energy consumption robust prediction [J]. Energy, 2018, 164: 137-146.
He Y L, Wang P J, Zhang M Q, et al. A novel and effective nonlinear interpolation virtual sample generation method for enhancing energy prediction and analysis on small data problem: A case study of Ethylene industry [J]. Energy, 2018, 147: 418-427.
Zhu Q X, Wang X, He Y L*, et al. An improved extreme learning machine integrated with nonlinear principal components and its application to modeling complex chemical processes [J]. Applied Thermal Engineering, 2018, 130: 745-753.
Zhang X, Zhu Q, Jiang Z Y, He Y L*, et al. A novel ensemble model using PLSR integrated with multiple activation functions based ELM: Applications to soft sensor development [J]. Chemometrics and Intelligent Laboratory Systems, 2018, 183: 147-157.
Gong H F, Chen Z S, Zhu Q X, He Y L*. A Monte Carlo and PSO based virtual sample generation method for enhancing the energy prediction and energy optimization on small data problem: An empirical study of petrochemical industries [J]. Applied energy, 2017, 197: 405-415.
Zhu Q X, Meng Q Q, He Y L*. Novel multidimensional feature pattern classification method and its application to fault diagnosis [J]. Industrial & Engineering Chemistry Research, 2017, 56(31): 8906-8916.

科研成果
数据高维特征映射


神经网络建模