何正磊

广东工业大学生态环境与资源学院副教授,硕士生导师。

邮箱:hezhenglei@scut.edu.cn

基本信息

法国里尔大学博士,广东工业大学“青年百人计划”A类引进人才。International Journal of Computational Intelligent systems期刊区域主编。主持或参与国家重点研发计划、国家自然科学基金等科研项目10余项,在Environmental Science & Technology、IEEE Transaction等生态环境领域和计算智能领域权威期刊发表论文40余篇,获中国纺织工业联合会科学技术进步奖等奖项。

研究方向

智能建模与智慧环境优化

数字智能驱动减污降碳协同增效

节能与清洁生产

多标准决策与多目标优化

数字孪生与AI大模型

数字化与智能化的环境系统工程应用

工作经历

2024.07-至今:广东工业大学生态环境与资源学院暨环境生态工程研究院,副教授

2021.07-2024.07:华南理工大学,助理研究员

教育经历

2017.09-2020.12:法国里尔大学,自动化与智能制造,博士

2014.09-2017.06:武汉纺织大学,纺织科学与工程,硕士

2016.07-2016.08:美国杜克大学,访学

2010.09-2014.06:武汉纺织大学,纺织工程,学士

学术兼职

International Journal of Computational Intelligent systems(欧洲模糊逻辑和技术学会会刊)区域主编

Advanced Materials & Sustainable Manufacturing编委

International Research Institute for Artificial Intelligence and Data Science, Dong A University国际主委委员

FLINS2022(Nankai University), DSBFI2023(Donga University), ISKE2023(Fujian Normal University), GCPC2023(Elsevier, Fudan University),EAIRAIDS2024(University of Lille)国际会议大会委员或分会场主席

Applied Science, Journal of Smart Environments and Green Computing, EAI Endorsed Transactions on AI and Robotic客座编辑

主要荣誉

中国纺织工业联合会科学技术进步奖

BEST PAPER AWARDofthe 19th Conference on Intelligence Systems and Knowledge Engineering2024

2024过程系统工程工程年会优秀论文奖

中国生态学学会产业生态专委会学术年会优秀学术报告奖

中国造纸2023年度优秀论文(两篇入围)

华南理工大学优秀班主任

国家公派留学奖学金

湖北省海外游学奖学金(杜克大学,美国)

研究生国家奖学金

武汉纺织大学优秀硕士学位论文

武汉纺织大学优秀毕业生

科研项目

广州市基础与应用基础研究(造纸工业过程的温室气体排放动态模拟方法研究)

国家地方联合工程实验室开放课题(牛仔清洁生产技术的集成与优化应用研究)

华南理工大学引智计划(Xianyi Zeng, Kim Phuc Tran, Rafiqul Gani)

国家重点研发计划(一带一路沿线典型重污染行业清洁生产技术比较与应用联合研究)

国家自然科学基金(造纸污水处理过程温室气体形成机制及减排调控模型研究)

广东省重点领域研发计划(面向陶瓷工业智能制造的工艺设计与生产工业软件研发)

人工智能与数字经济广东省实验室(广州)青年学者项目(基于人工智能的工业过程用电预测与预购电策略)

中央高校基本科研业务费专项资金资助(工业系统的多尺度环境分析模型与生态调控)

制浆造纸工程国家重点实验室重点项目(造纸生产过程数字孪生关键技术研究)

代表性科研成果

(一)论文发表

1.He, Z.,Z. Lu,X. Wang,Q.Xiong, K. Tran, S. Thomassey, X. Zeng, M. Hong and Y. Man(2024).Multi-objective Optimization of Papermaking Wastewater Treatment Processes Under Economic, Energy, and Environmental Goals.Environmental Science &Technology,(Accept).

2.He, Z.,S. Li,Y.Wang,B.Chen,J.Ren,Q.Xiong,Y.Man(2024).Interpretable GHG emission prediction for papermaking wastewater treatment process with deep learning.Chemical Engineering Science,Available online 10 July 2024, 120492.https://doi.org/10.1016/j.ces.2024.120492

3.Bi, H.,Zhao X.,Xu D.,Liu J.,He, Z*.,An L., Zhu B., Sun C.,LiZ. (2024)Differences in anodizing of two copper-containing coordination compounds by different degradation factors: experiments and DFT calculations.Journal of Cleaner Production,Available online 21 June 2024, 142969https://doi.org/10.1016/j.jclepro.2024.142969

4.Liang, X., Zhang, Q.,Man, Y.,He, Z*. (2024) Toward sustainable process industry based on knowledge graph: a case study of papermaking.Discover Sustainability,5:93.https://doi.org/10.1007/s43621-024-00259-6

5.He, Z.,C. Liu, Y. Wang, X.Wang,and Y. Man (2023). Optimal operation of wind-solar-thermal collaborative power system considering carbon trading and energy storage.Applied Energy, 352: 121993.https://doi.org/10.1016/j.apenergy.2023.121993

6.He, Z., M. Hong, H. Zheng, J. Wang, Q. Xiong, and Y. Man (2023). Towards Low-carbon Papermaking Wastewater Treatment Process based on Kriging Surrogate Predictive Model.Journal of Cleaner Production, 425: 139039.https://doi.org/10.1016/j.jclepro.2023.139039

7.Man, Y., Yan, Y., Ren, J., Wang, X., Xiong, Q., &He, Z*(2023). Overestimated Carbon Emission of the Pulp and Paper industry in China.Energy, 273: 127279.https://doi.org/10.1016/j.energy.2023.127279

8.He, Z., Chen, G., Hong, M. Xiong, Q., Zeng X., & Man, Y. (2023) Process Monitoring and Fault Prediction of Papermaking by Learning from Imperfect Data.IEEE Transactions on Automation Science and Engineering(Early Access).https://doi.org/10.1109/TASE.2023.3290552

9.Zhang, Z., He, X., Man, Y.,&He, Z*.(2023) Multi-objective scheduling in dynamic of household paper workshop considering energy consumption in production process.Journal of Smart Environments and Green Computing, 3:87-105.http://dx.doi.org/10.20517/jsegc.2023.05

10.He, Z., Tran, K. P., Thomassey, S., Zeng, X., Xu, J., & Changhai, Y. (2022) Multi-Objective Optimization of the Textile Manufacturing Process Using Deep-Q-Network Based Multi-Agent Reinforcement Learning.Journal of Manufacturing Systems, 62: 939-949.https://doi.org/10.1016/j.jmsy.2021.03.017

11.He, Z., Qian, J, Man, Y., Li, J., & Hong, M.(2022)Data-driven soft sensors of papermaking process and its application to cleaner production with multi-objective optimization.Journal of Cleaner Production,372: 133803.https://www.sciencedirect.com/science/article/pii/S0959652622033790

12.Zhang, H.,Li, J., Hong, M.,Man, Y., &He, Z*. (2022) Cost Optimal Production-Scheduling Model Based on VNS-NSGA-II Hybrid Algorithm—Study on Tissue Paper Mill.Processes,2022, 10: 2072.https://doi.org/10.3390/pr10102072

13.He, Z., Tran, K. P., Thomassey, S., Zeng, X., Xu, J., & Changhai, Y. (2021) Modeling of Textile Manufacturing Processes Using intelligent techniques: a review.International Journal of Advanced Manufacturing Technology,116, 39–67. https://link.springer.com/article/10.1007/s00170-021-07444-1

14.Xu, J., Liu, F,He, Z*., Li, S. (2021).Cost Optimization of Sodium Hypochlorite Bleaching Washing for Denim by Combining Ensemble of Surrogates with particle swarm optimization.Journal of Engineered Fibers and Fabrics.https://doi.org/10.1177/15589250211022331

15.HE, Z., TRAN, K. P., THOMASSEY, S., ZENG, X., XU, J., & YI, C. (2021) A Deep Reinforcement Learning Based Multi-Criteria Decision Support System for Optimizing Textile Chemical Process.Computers in Industry,125(February 2021): 103373https://doi.org/10.1016/j.compind.2020.103373.

16.Xu, J., Liu, F,He, Z*., Li, S. (2021).Cost Optimization of Sodium Hypochlorite Bleaching Washing for Denim by Combining Ensemble of Surrogates with particle swarm optimization.Journal of Engineered Fibers and Fabrics.https://doi.org/10.1177/15589250211022331

17.He, Z., Tran, K. P., Thomassey, S., Zeng, X., Xu, J., & Changhai, Y. (2020). Modeling color fading ozonation of reactive-dyed cotton using the Extreme Learning Machine, Support Vector Regression and Random Forest.Textile Research Journal,90(7-8), 896-908.https://doi.org/10.1177/0040517519883059

18.Xu, J.,He, Z*., Li, S., & Ke, W. (2020). Production cost optimization of enzyme washing for indigodyed cotton denim by combining Kriging surrogate with differential evolution algorithm.Textile Research Journal,90(15-16): 1860-1871.https://doi.org/10.1177/0040517520904352

19.He, Z., Li, M., Zuo, D., Xu, J., & Yi, C. (2019) Effects of color fading ozonation on the color yield of reactive-dyed cotton.Dyes and Pigments,164, 417-427.https://doi.org/10.1016/j.dyepig.2019.01.006

20.He, Z.,Li, M., Zuo, D., & Yi, C. (2019). Color fading of reactive-dyed cotton using UV-assisted ozonation.Ozone: Science & Engineering,41(1), 60-68.https://doi.org/10.1080/01919512.2018.1483817

21.He, Z., Li, M., Zuo, D., & Yi, C. (2018). The effect of denim color fading ozonation on yarns.Ozone: Science & Engineering,40(5), 377-384.https://doi.org/10.1080/01919512.2018.1435259

22.李世忠,满奕,何正磊*.(2024)基于DNN-LSTM的造纸污水处理过程温室气体排放分析模型,中国造纸.2024,43(04):170-176.

23.陈国健,李继庚,陈波,满奕,何正磊*. (2024)基于自编码的长流程造纸过程断纸故障识别,中国造纸. 2024,43(03):113-120+141.

24.朱小林,刘昌,满奕,何正磊*. (2024)考虑碳交易和储能系统的风光火协同优化运行,华北电力大学学报. (网络首发)

25.刘昌,朱小林,满奕,何正磊*. (2023)面向造纸园区的多能协同调度模型,中国造纸, 42(12):158-169.

26.陆造好,满奕,李继庚,洪蒙纳,何正磊*.(2023)基于深度强化学习的造纸废水处理过程多目标优化,中国造纸,42(3):13-22.

27.钱继炜,李继庚,满奕,洪蒙纳,何正磊*. (2023)基于机器学习的箱纸板质量离线软测量建模研究,中国造纸. 42(07): 72-78+129.

28.张一水,满奕,何正磊*. (2023)造纸工业过程数字孪生模型的构建与应用,造纸科学与技术, 42(5): 1-7.

(二)专利

何正磊;满奕;刘泽君.瓷砖坯体干燥过程中坯体温湿度变化的模拟系统及方法, 2024-7-5,中国, CN202410953459.7

何正磊;满奕;刘泽君.一种陶瓷生坯热风干燥过程的模拟方法, 2024-7-5,中国, CN 2024108956732.3

满奕;何正磊;陆造好.一种基于强化学习的造纸污水处理优化控制方法, 2023-12-08,中国, CN202311687078.0

满奕;何正磊;张振亚.一种建筑陶瓷质量小试的辅助配料预测方法,2024-7-5,中国, CN202410895687.3

满奕;何正磊;张振亚.一种基于机器学习的建筑陶瓷烧成形变预测方法,2024-7-5,中国, CN202410895808.4

满奕;何正磊;张振亚.一种基于机器学习实现建筑陶瓷坯体小试质量预测的方法,2024-7-5,中国, CN202410895865.2


(三)专著、章节

Tran, K.,He, Z.(2024)Computational Techniques for Smart Manufacturing in Industry 5.0: Methods and Applications.CRC Press, Taylor & Francis Group, USA.

Chen, G.,He, Z*., Man, Y., Li, J., & Hong, M. (2023) Fault Prediction of Papermaking Process Based on Gaussian Mixture Model and Mahalanobis Distance. In Artificial Intelligence for Smart Manufacturing: Methods, Applications, and Challenges (pp. 83-96). Springer, Cham.

Zhang, H.,He, Z*., Man, Y., Li, J., & Hong, M. (2023) Multi-objective optimization of flexible flow-shop intelligent scheduling based on hybrid intelligent algorithm. In Artificial Intelligence for Smart Manufacturing: Methods, Applications, and Challenges (pp. 97-117). Springer, Cham.

Lu, Z.,He, Z.*, Tran, K. P., Thomassey, S., Zeng, X., & Hong, M. (2022) Decision Support Systems for Textile Manufacturing Process with Machine Learning. In Machine Learning and Probabilistic Graphical Models for Decision Support Systems (pp. 107-121). CRC Press, Taylor & Francis Group, USA.

He, Z.*, Tran, K. P., Thomassey, S., Zeng, X., & Yi, C. (2020). Application of Artificial Intelligence in Modeling a Textile Finishing Process. In Reliability and Statistical Computing (pp. 61-84). Springer, Cham.


(四)会议

胡丁丁,何正磊*.基于Kriging-HDMR多智能体强化学习的造纸污水处理过程多目标优化, 2024过程系统工程年会,大连.

Hu D., Chen G.,He, Z*.,Tran K., Zeng X.Paper Break Fault Recognition in Long ProcessofPapermaking Based on Autoencoder,16th International FLINS Conference on Robotics and Artificial Intelligence (FLINS 2024),Madrid, Spain.

He, Z.Modeling and dynamic optimization of carbon emission in the papermaking process, in Global Cleaner Production Conference 2023, Shanghai, China, (特邀报告).

Lu, Z., Hong, M., Man, Y., Zeng. X., &He, Z*. (2023).Reinforcement Learning Method for Multi-objective Optimization of Papermaking Wastewater Treatment Process.InProceedings of the 18th International Conference on Intelligent Systems and Knowledge Engineering (ISKE 2023), Fuzhou, China.

He, Z.Reducing Carbon Emission of Papermaking Process through data-driven models and multi-agent reinforcement learning.2022 International Workshop on Cleaner Production & Carbon Neutrality in the Belt and Road Initiative, Guangzhou, China.

Qian, J., Zhang, Y.,He, Z*., Man, Y., Li, J., & Hong, M. (2022).Influence of potential multi-condition data on soft sensor modeling. InProceedings of the 15th International FLINS Conference on Robotics and Artificial Intelligence (FLINS 2022),Tianjin, China.

Zhang, Y., Qian, J.,He, Z*., Man, Y., Li, J., & Hong, M. (2022).Digital twin for energy optimization in the paper drying process based on genetic algorithm and CADSIM Plus. InProceedings of the 15th International FLINS Conference on Robotics and Artificial Intelligence (FLINS 2022),Tianjin, China.

何正磊,人工智能技术赋能牛仔服装清洁生产与碳减排,2021中国牛仔时尚产业可持续发展高峰论坛,于都(特邀报告).

何正磊,基于多智能体深度强化学习的造纸污水处理过程多目标优化, 2021中国生态学学会产业生态学专委会学术年会,上海.

He, Z., Tran, K. P., Thomassey, S., Zeng, X., & Yi, C. (2020). A reinforcement learning based decision support system in textile manufacturing process. InProceedings of the 14th International FLINS Conference on Robotics and Artificial Intelligence (FLINS 2020),Cologne, Germany.

He, Z., Tran, K. P., Thomassey, S., Zeng, X., & Yi, C. (2019). Modeling Color Fading Ozonation of Textile Using Artificial Intelligence. InISSAT International Conference on Data Science in Business, Finance and Industry (DSBFI 2019),Danang, Vietnam.

He, Z., Thomassey, S., Zeng, X., Zuo, D., & Yi, C. (2018). The application of process modeling in denim manufacturing. InProceedings of the 13th International Conference on Data Science and Knowledge Engineering for Sensing Decision Support (FLINS 2018),Belfast, UK.

He, Z., Zhou, X., Zuo, D., & Yi, C. (2017).Ozone/UV Collaborative Treatment on the Color Fading of Dyed Cotton. In Proceedings of the 10thTextile Bioengineering and Informatics Society (TBIS2017), Wuhan, China.

Li, M.,He, Z,Cui, T., Wu, Z., Wu, J. (2017).Determination of the content of calcium oxalate crystals in antheraea pernyi cocoon layers based on the inductively coupled plasma-atomic emission spectrometry. Proceedings of the 10thTextile Bioengineering and Informatics Society (TBIS2017), Wuhan, China.

Du, W., Li, T.,He, Z., Zuo, D., Zou, H., Wang, X., & Yi, C. (2015).Comparative assessment of denimgarments treated with laser bleaching and enzymatic bleaching methods. In The Fiber Society 2015 Fall Meeting and Technical Conference,Raleigh, USA.

联系方式

所在杨志峰院士团队,欢迎有环境科学与工程、经济管理、系统工程、工业工程、统计学、数据科学、计算机等专业背景的学生报考硕士研究生!欢迎感兴趣的本科生加入课题组!

联系地址:广东省广州市番禺区广州大学城外环西路100号广东工业大学生态环境与资源学院

联系方式:hezhenglei@scut.edu.cn

邮政编码:510006

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