Preprint   (* indicates the corresponding author.)

• Yanxin Chen, Cuimei Bo, Guo. Yu, Furong Gao, Hui Wan, Xiaoqian Ren, "Multi-objective optimization decision-making for the C4 alkylation hydrogenation reaction under safety constraints " submitted, 2026.

• Shida Gao, Cuimei Bo, Zijun Wang, Guo. Yu, Furong Gao, Genke Yang, Jian Chu, Dynamic Multi-objective Operation Optimization of Dimethyl Oxalate Hydrogenation Process under Green Hydrogen Flow Fluctuation, submitted, 2025.

• Chao Jiang, Weimin Zhong, G. Yu*, Xin Peng, Dayu Tan, Zhi Li, Minxue Kong, Quality-Related Probabilistic Slow Feature Extraction for Semisupervised Inferential Modeling with Incomplete Data, submitted, 2023.

• Chao Jiang, Lin Shi, Cheng Yang, Zehui Song, Guo Yu*, "Transferable Adversarial Long Sequence Analysis for Few-shot Multi-step Quality Prediction in Coal-to-Ethylene Glycol Process" , submitted, 2024.

• Qian Ying; Ma Lianbo; Wang Liang; Guo Yu; Zheng Meng; Huang Min; Li Qing, "UOIM: Online Incentive Design for Fair Hierarchical Federated Learning and Unlearning in Edge Computing" , Submitted, 2024.

• Chao Jiang, Guo Yu*, Zhi Li, Minxue Kong, Dayu Tan, Weimin Zhong, "Temporal-aware quality-relevant probabilistic slow feature analysis for semisupervised inferential modeling with irregularly sampled data" , Control Engineering Practice, Submitted, 2024.

• Chao Jiang, Guo Yu*, Dayu Tan, Cheng Su, Weimin Zhong, "Temporal-Aware Slow Feature Extraction with Reinforcement Learning-Based Delay Estimation for Inferential Modeling under Irregular Sampling" , TSMC-A, Submitted, 2024.

• Chao Jiang, Guo Yu*, Weimin Zhong, "Robust quality-relevant slow feature extraction for industrial inferential modeling" , Journal of Process Control, Submitted, 2024.

Journal Papers

AI for Chemical Engineering

• G. Yu, L. Ma, W. Du, Chao Jiang, Quanling Zhang, "Transferable preference learning in multi-objective decision analysis and its application to hydrocracking " Complex & Intelligent Systems, 2024. doi:10.1007/s40747-024-01537-6.

• G. Yu, Dongjie Zhang, Hailong Deng, Chao Jiang, Quanling Zhang, "Operation Optimization of Multiphase Pollutant Treatment Considering Carbon Emissions," in IEEE Access，2024. doi: 10.1109/ACCESS.2024.3410325

• Xiangyu Zeng, Cuimei Bo*, G. Yu*, Quanling Zhang, Xu Qiao, Furong Gao, Multi-objective decision analysis for acrylic acid purification process considering economic benefits and carbon reduction, in Journal of Cleaner Production , Volume 164, November 2025, 106476

• Jinwen Pan, Guo Yu*, Cuimei Bo, Shuhua Huang, Lianbo Ma, and Zhongfu An, Feature-Decoupled Multi-Task Graph Attention Network for Chemical Process Fault Classification and Localization, in Measurement Science and Technology , 2026. doi: 10.1088/1361-6501/ae412e

• 曾祥宇, 薄翠梅*, 喻果*, 张泉灵, 基于自适应采集函数的丙烯酸生产过程代理模型, 控制理论与应用, 2026. Accepted

• Jinrong Qi, Mingguang Zhang, Guo Yu, Cuimei Bo, "Analysis and Intelligent Prediction of Domino Effect Accidents in Chemical Storage Tanks with a Focus on Accident Chain Length", PLoS One, 2025, 20(9): e0331180. https://doi.org/10.1371/journal.pone.0331180

• Cheng Yang, Chao Jiang, G. Yu, Jun Li, and Cuimei Bo, "APSF-Net: A Deep Adversarial Slow Feature Extraction Network for Industrial Inferential Modeling," Control Engineering Practice, Control Engineering Practice, 2024, 147: 105934.

• Cheng Yang, Chao Jiang, G. Yu, Jun Li, Cuimei Bo, "Transferable Adversarial Slow Feature Extraction Network for Few-Shot Quality Prediction in Coal-to-Ethylene Glycol Process", Chinese Journal of Chemical Engineering, 2024, ISSN 1004-9541

• Shida Gao, Cuimei Bo*, Guo Yu, Quanling Zhang, Genke Yang*, Jian Chu, "Multi-objective optimization of carbon emissions and economic benefits in green hydrogen-coupled dimethyl oxalate hydrogenation process", International Journal of Hydrogen Energy, Volume 165, 5 September 2025, 150869, 2025. https://doi.org/10.1016/j.ijhydene.2025.150869

• Shida Gao, Cuimei Bo, G. Yu, Quanling Zhang, Furong Gao, Genke Yang, Jian Chu, "Multi-objective optimization for sustainable dimethyl oxalate synthesis: A plant-wide framework balancing economic benefits and carbon emissions", Chemical Engineering Research and Design, 2026. Volume 226, February 2026, Pages 536-549.

Preference-driven/ Fairness-Aware Optimization

• G. Yu, L. Ma, Xilu Wang, W. Du, W. Du, Y. Jin, "Toward Fairness-Aware Multi-Objective Optimization" Complex & Intelligent Systems, Volume 11, article number 50, (2025).

• G. Yu, L. Ma, Y. Jin*, W. Du*, Q. Liu and H. Zhang, "A Survey on Knee-oriented Multi-objective Evolutionary Optimization," in IEEE Transactions on Evolutionary Computation, vol. 26, no. 6, pp. 1452-1472, Dec. 2022, doi: 10.1109/TEVC.2022.3144880.

• G. Yu, Y. Jin*, M. Olhofer, Q. Liu and W. Du, "Solution Set Augmentation for Knee Identification in Multiobjective Decision Analysis," in IEEE Transactions on Cybernetics, vol. 53, no. 4, pp. 2480-2493, April 2023, doi: 10.1109/TCYB.2021.3125071. Code

• G. Yu, Y. Jin*, M. Olhofer, "A Multiobjective Evolutionary Algorithm for Finding Knee Regions Using Two Localized Dominance Relationships," in IEEE Transactions on Evolutionary Computation, vol. 25, no. 1, pp. 145-158, Feb. 2021, doi: 10.1109/TEVC.2020.3008877. Code

• G. Yu, Y. Jin*, M. Olhofer, "Benchmark Problems and Performance Indicators for Search of Knee Points in Multiobjective Optimization," in IEEE Transactions on Cybernetics, vol. 50, no. 8, pp. 3531-3544, Aug. 2020, doi: 10.1109/TCYB.2019.2894664. Code

• G. Yu, J. Zheng*, R. Shen, M. Li, "Decomposing the user-preference in multiobjective optimization," in Soft Computing, vol. 20, no. 10, pp. 4005–4021, 2016, https://doi.org/10.1007/s00500-015-1736-z. Code

• J. Zheng, G. Yu*, Q. Zhu, X. Li, J. Zou, "On decomposition methods in interactive user-preference based optimization," in Applied Soft Computing, vol. 52, pp. 952-973, 2017, https://doi.org/10.1016/j.asoc.2016.09.032.

• 郑金华, 喻果*, 贾月. 基于权重迭代的偏好多目标分解算法解决参考点对算法影响的研究[J]. 电子学报, 2016, 44(1): 67-76 https://doi.org/10.3969/j.issn.0372-2112.2016.01.011

  J. Zheng, G. Yu*, Y. Jia, "Research on MOEA/D based on user-preference and alternate weight to solve the effect of reference point on multi-objective algorithms," in Acta Electronica Sinica, vol. 44, no. 1, pp. 67-76, 2016, DOI: 10.3969/j.issn.0372-2112.2016.01.011.

• J. Hu, G. Yu, J. Zheng, J. Zou, "A preference-based multi-objective evolutionary algorithm using preference selection radius," in Soft Computing, vol. 21, pp. 5025–5051, 2017, https://doi.org/10.1007/s00500-016-2099-9.

• 王帅发,郑金华*,胡建杰,邹娟,喻果.自适应偏好半径划分区域的多目标进化方法.软件学报,2017,28(10):2704-2721

  S. Wang, J. Zheng, J. Hu, J. Zou, G. Yu, "Multi-objective evolutionary algorithm for adaptive preference radius to divide region," in Journal of Software, vol. 28, no. 10, pp. 2704-2721, 2017, http://www.jos.org.cn/jos/article/abstract/5307.

Multi-/Many-objective Optimization

• G. Yu, R. Shen, J. Zheng*, M. Li, J. Zou, Y. Liu, "Binary search based boundary elimination selection in many-objective evolutionary optimization," in Applied Soft Computing, vol. 60, pp. 689-705, 2017, https://doi.org/10.1016/j.asoc.2017.07.030.

• Lianbo Ma, Yang Liu, G. Yu*, Xinzhe Wang, Hongwei Mo, Gai-Ge Wang, Yaochu Jin, Ying Tan, "Decomposition-based multiobjective optimization for variable-Length mixed-variable Pareto optimization and its application in cloud service allocation," in IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2023, DOI 10.1109/TSMC.2023.3295371. Code

• Q. Liu, Y. Jin, M. Heiderich, T. Rodemann, G. Yu, "An adaptive reference vector-guided evolutionary algorithm using growing neural gas for many-objective optimization of irregular problems," in IEEE Transactions on Cybernetics, Oct. 2020, DOI: 10.1109/TCYB.2020.3020630.

• D. han, W. Du, Y. Jin, W. Du, G. Yu, "A fuzzy constraint handling technique for decomposition-based constrained multi- and many-objective optimization," in Information Science, vol. 597, pp.318-340, June 2022, https://doi.org/10.1016/j.ins.2022.03.030.

• H. Bai, J. Zheng, G. Yu, S. Yang, J. Zou, "A Pareto-based many-objective evolutionary algorithm using space partitioning selection and angle-based truncation," in Information Sciences, vol. 478, pp. 186-207, 2019, https://doi.org/10.1016/j.ins.2018.10.027.

• J. Zou, L. Fu, J. Zheng, S. Yang, G. Yu, Y. Hu, "A many-objective evolutionary algorithm based on rotated grid," in Applied Soft Computing, vol. 478, pp. 186-207, 2019, https://doi.org/10.1016/j.asoc.2018.02.031.

• 刘元, 郑金华*, 邹娟, 喻果. 基于邻域竞赛的多目标优化算法. 自动化学报, 2018, 44(7): 1304-1320. doi: 10.16383/j.aas.2017.c160315

  Y. liu, J. Zheng, J. Zou, G. Yu, "An evolutionary algorithm through neighborhood competition for multi-objective optimization," in Acta Electronica Sinica, vol. 44, no. 7, pp. 1304-1320, 2018, http://www.aas.net.cn/cn/article/doi/10.16383/j.aas.2017.c160315.

Evolutionary Deep Learning

• Lianbo Ma, Nan Li, Guo Yu*, Xiaoyu Geng, Shi Cheng, Xingwei Wang, Min Huang, Yaochu Jin, "Pareto-wise Ranking Classifier for Multi-objective Evolutionary Neural Architecture Search", in IEEE Transactions on Evolutionary Computation, 2023, DOI: 10.1109/TEVC.2023.3314766

• Lianbo Ma, Yuee Zhou, Ye Ma, Guo Yu*, Qing Li, Qiang He, and Yan Pei, "Defying Multi-model Forgetting in One-shot Neural Architecture Search Using Orthogonal Gradient Learning", in IEEE Transactions on Computers, pp. 1-13, 2025. https://doi.org/10.1109/TC.2025.3540650

• Ma Lianbo, Kang Haidong, Guo Yu*, Li Qing, He Qiang, "Single-Domain Generalized Predictor for Neural Architecture Search System", in IEEE Transactions on Computers , vol. 73, no. 5, pp. 1400-1413, May 2024, doi: 10.1109/TC.2024.3365949.

• N. Li, L. Ma*,G. Yu, Bing Xue, Mengjie Zhang, Yaochu Jin "Survey on Evolutionary Deep Learning: Principles, Algorithms, Applications and Open Issues" ACM Computing Survey, 2023.

• Jian Cheng, Tian Zhang, Shuang Zhang, Huimin Ren, Guo Yu*, Xiliang Zhang, and Shangce Gao, and Lianbo Ma, "A Cascade Dual-Decoder Model for Joint Entity and Relation Extraction", IEEE Transactions on Emerging Topics in Computational Intelligence, 2024. doi: 10.1109/TETCI.2024.3406440.

• Lianbo Ma, Nan Li, Peican Zhu, Keke Tang, Asad Khan, Feng Wang, G. Yu, "A Novel Fuzzy Neural Network Architecture Search Framework for Defect Recognition with Uncertainties," IEEE Transactions on Fuzzy Systems, 2024. doi: 10.1109/TFUZZ.2024.3373792.

• X. Quan, N. Zhang, G. Yu*, Q. Liu, L. Ma, "Prediction of air leakage rate of sintering furnace based on BP neural network optimized by PSO," Wireless Communications and Mobile Computing , vol. 2022, Article ID 5631787, 9 pages, 2022. https://doi.org/10.1155/2022/5631787. Code

• S. Liu, N. Zhang, G. Yu*, "Lightweight Security Wear detection method based on YOLOv5," Wireless Communications and Mobile Computing , vol. 2022, Article ID 1319029, 14 pages, 2022. https://doi.org/10.1155/2022/1319029. Code

• G. Xie, J. Wang, G. Yu, Jiayi Lyu, F. Zheng, Y. Jin, "Tiny adversarial mulit-objective oneshot neural architecture search," Complex & Intelligent System, 2023. https://doi.org/10.1007/s40747-023-01139-8

• Hengmin Zhang, Bihan Wen, Zhiyuan Zha, Bob Zhang, Yang Tang, G. Yu, Wenli Du, "Accelerated PALM for Nonconvex Low-rank Matrix Recovery with Theoretical Analysis," IEEE Transactions on Circuits and Systems for Video Technology, Accepted, 2023.

• Rui Ding, Xiaoping Zhou, Dayu Tan, Yansen Su, Chao Jiang, Guo Yu, Chunhou Zheng, "A Deep Multi-Branch Attention Model for Histopathological Breast Cancer Image Classification," in Complex & Intelligent Systems, 2024. https://doi.org/10.1007/s40747-024-01398-z

• Nan Li, Lianbo Ma, Tiejun Xing, G. Yu, Chen Wang, Yingyou Wen, Shi Cheng, Shangce Gao, "Automatic design of machine learning via evolutionary computation: A survey," Applied Soft Computing, Available online 18 May 2023, 110412. https://doi.org/10.1016/j.asoc.2023.110412

Dynamic Multi-objective Optimization

• X. Zhang, G. Yu*, Y. Jin, F. Qian, "Elitism-based Transfer Learning and Diversity Maintenance Strategies for Dynamic Multi-objective Optimization," Information Science, 2023, Volume 636, July 2023, 118927. https://doi.org/10.1016/j.ins.2023.04.006

• X. Zhang, G. Yu*, Y. Jin, F. Qian, "An Adaptive Kriging Model Based Manifold Transfer Learning to Expensive Dynamic Multi-Objective Optimization," Neurocomputing , 2023, Volume 538, 14 June 2023, 126212. https://doi.org/10.1016/j.neucom.2023.03.073. .

• G. Ruan, G. Yu*, J. Zheng, J. Zou, S. Yang, "The effect of diversity maintenance on prediction in dynamic multi-objective optimization," in Applied Soft Computing, vol. 58, pp. 631-647, 2017, https://doi.org/10.1016/j.asoc.2017.05.008.

Large-scale Optimization/Scheduling

• G. Yu,Yibo Yong, Chao Jiang, Fei Hao, Lianbo Ma, "Formal concept analysis assisted large-scale global optimization and its application to cloud task scheduling," Complex & Intelligent System, 11, 245 (2025). https://doi.org/10.1007/s40747-025-01878-w. Code

• W. Zhang, W. Du, G. Yu, R. He, Y. Jin, W. Du, "Knowledge-Assisted Dual-Stage Evolutionary Optimization of Large-Scale Crude Oil Scheduling," IEEE Transactions on Emerging Topics in Computational Intelligence, 2024. doi: 10.1109/TETCI.2024.3353590.

• Wenxuan Fang, Wei Du, Guo Yu, Renchu He, and Yaochu Jin, "Preference Prediction-based Evolutionary Multi-objective Optimization for Gasoline Blending Scheduling", in IEEE Transactions on Artificial Intelligence, vol. 6, no. 1, pp. 79-92, Jan. 2025, doi: 10.1109/TAI.2024.3444736.

• Yunning Yang, Renchu He, G. Yu, Wei Du, Minglei Yang, Wenli Du, "Efficient rolling horizon approach to a crude oil scheduling problem for marine-access refineries," in Computers & Chemical Engineering, 2023, 108121, ISSN 0098-1354,.

Federated Learning/Optimization

• Lianbo Ma, Ying Qian, Guo Yu, Zhetao Li, Liang Wang, Qing Li, Xingwei Wang, and Guangjie Han, "TBCIM: Two-Level Blockchain-Aided Edge Resource Allocation Mechanism for Federated Learning Service Market", IEEE Transactions on Networking , 2025, doi: 10.1109/TON.2025.3589017.

• Qiqi Liu, Yuping Yan, Yaochu Jin, Xilu Wang, Peter Ligeti, Guo Yu, Xueming Yan, "Secure Federated Evolutionary Optimization—A Survey," Engineering, 7 December 2023. https://doi.org/10.1016/j.eng.2023.10.006

Single-objective Optimization

• X. Zhou, J. Tian, J. Long, Y. Jin, G. Yu, C. Yang, "A fast constrained state transition algorithm," in Neurocomputing, vol.455, pp.202-214, 2021, https://doi.org/10.1016/j.neucom.2021.05.053.

Conference Papers

AI for Chemical Engineering

• Jiajia Shen, Jiahao Chen, Guo. Yu, Cuimei Bo, Risk Assessment and Evolution Analysis of Fluid Catalytic Cracking Unit Based on ISM–BN Model, the 38th Chinese Control and Decision Conference (CCDC 2026), 2026.

• Xiangyu Zeng, Guo. Yu, Quanling Zhang, Cuimei Bo, An Adaptive Batch-ParEGO Algorithm with Reward Mechanism for Expensive Multi-Objective Optimization, the 38th Chinese Control and Decision Conference (CCDC 2026), 2026.

• Zehui Song, Zhuocheng Wang, G. Yu, Chao Jiang, Jun Li, Cuimei Bo, Sequential Variational Autoencoder for Industrial Inferential Modeling, 2025 7th International Conference on Data-driven Optimization of Complex Systems (DOCS), Taiyuan, China, 2025.

• Hailong Deng, Dongjie Zhang, Xiangyu Zeng, Guo Yu*, Quanling Zhang "A High-Fidelity Surrogate Model for Production Process of Dimethyl Oxalate", 2025 5th International Conference on Artificial Intelligence and Industrial Technology Applications, Xian, China. Accepted.

• Jingxuan Zhang, Guo Yu*, Cuimei Bo, Jun Li, "Data-driven dynamic modeling and fault diagnosis of dimethyl oxalate industrial production process", 2024 6th International Conference on Data-driven Optimization of Complex Systems (DOCS), Hangzhou, China, 2024, pp. 250-255, doi: 10.1109/DOCS63458.2024.10704444.

• 江超, 喻果*, 谭大禹, 基于切换概率慢特征提取的加氢裂化过程推断建模,2023中国化工学会年会，2023.（*优秀论文*）

• Yang Liu, G. Yu, Jian Chen, Chao Jiang, Xinzhe Wang, Lianbo Ma, Transferable Preference Learning Assist Multi-Objective Decision Analysis for Hydrocracking, 2023 5th International Conference on Data-driven Optimization of Complex Systems (DOCS), Tianjin, China, 2023, pp. 1-8, doi: 10.1109/DOCS60977.2023.10294748.

Preference-driven/ Fairness-Aware Optimization

• G. Yu, Wenli Du, "Interactive and interpretable knee point-driven multiobjective optimization for multiobjective decision making," in Proceedings of Chinese Automation Congress (CAC), Beijing, China, 2021, pp. 3168-3173, doi: 10.1109/CAC53003.2021.9727710.

• G. Yu, Y. Jin and M. Olhofer, "References or Preferences – Rethinking Many-objective Evolutionary Optimization," in Proceedings of 2019 IEEE Congress on Evolutionary Computation (CEC), Wellington, New Zealand, 2019, pp. 2410-2417.

• G. Yu, Y. Jin and M. Olhofer, "A Method for a Posteriori Identification of Knee Points Based on Solution Density," in Proceedings of 2018 IEEE Congress on Evolutionary Computation (CEC), Rio de Janeiro, 2018, pp. 1-8.

• G. Yu, Y. Jin and M. Olhofer, "An a priori knee identification multi-objective evolutionary algorithm based on α-dominance," in Proceedings of the Genetic and Evolutionary Computation Conference Companion (GECCO), July 2019, pp. 241–242.

• G. Yu, J. Zheng, and X. Li, "An improved performance metric for multiobjective evolutionary algorithms with user preferences," in Proceedings of 2015 IEEE Congress on Evolutionary Computation (CEC), Sendai, Japan, 2015, pp. 908-915.

• Z Hou, S Yang, J Zou, J Zheng, G. Yu, G Ruan, "A performance indicator for reference-point-based multiobjective evolutionary optimization," in Proceedings of 2018 IEEE Symposium Series on Computational Intelligence (SSCI), Bangalore, India, 2018, pp. 1571-1578.

Neural Network Quantization/Depression

• Ma L, Zhou Y, Ma J, Yu G. *, Li Q. One-Step Forward and Backtrack: Overcoming Zig-Zagging in Loss-Aware Quantization Training, in Proceedings of the AAAI Conference on Artificial Intelligence (AAAI) . 2024, 38. *Suppmentary material*

• Haidong Kang, Lianbo Ma, Guo Yu, Shangce Gao " Where and How to Enhance: Discovering Bit-Width Contribution for Mixed Precision Quantization", 2025 International Joint Conference on Artificial Intelligence (IJCAI), Montreal, Quebec, Canada. Accepted.

Evolutionary Deep Learning

• Haidong Kang, Lianbo Ma, Pengjun Chen Guo Yu, Xingwei Wang, Min Huang "Beyond the Limits: Overcoming Negative Correlation of Activation-Based Training-Free NAS", International Conference on Computer Vision 2025 (ICCV), Honolulu, Hawaii, America. Accepted.

• Kaifang Long, Lianbo Ma, Yang Gao, Guo Yu, "Feature Stacking Fusion in Multimodal Neural Architecture Search", 2024 6th International Conference on Data-driven Optimization of Complex Systems (DOCS), Hangzhou, China, 2024, pp. 414-419, doi: 10.1109/DOCS63458.2024.10704481.

Large-scale Optimization/Scheduling

• W. Zhang, W. Du, G. Yu, R. He, W. Du, "Large-scale crude oil scheduling: A framework of hybrid optimization based on plan decomposition," 2022 IEEE Congress on Evolutionary Computation (CEC), 2022, pp. 1-8, doi: 10.1109/CEC55065.2022.9870364..

专利

• 杜文莉; 堵威; 何仁初; 喻果; 钟伟民; 钱锋 ; 一种基于原油调合模型的原油调度方案优化方法, 2022-09-30, 中国, CN202211208919.0.

• 喻果；江超；杨澄；薄翠梅；一种用于煤制乙二醇过程的小样本质量预测方法，2023, 中国.CN202311298880.0.

• 喻果,江超,杨澄,等.一种基于深度对抗慢特征提取网络的化工过程推断建模方法:202311364399[P][2025-11-17].

• 薄翠梅;叶胜利;李俊;王玉;张贺;喻果；一种精馏塔分层经济优化预测控制方法，2024, 中国, CN202411446268.8

• 薄翠梅;施霖;高世达;李俊;喻果；一种基于迁移学习与稀疏自注意力的化工过程关键参数成分预测方法，2025, 中国, CN202510345260.0

• 薄翠梅;张婧瑄;喻果;李俊；一种基于动态加权投票的联邦学习的故障诊断方法，2025, 中国, CN202511137279.2

• 薄翠梅;陈艳欣;任晓乾;李俊;喻果;一种用于碳四烷基化加氢反应过程的多目标优化方法，2025, 中国, CN202511511285.X

标准

• DB32/T 4679—2024 生活垃圾焚烧发电厂烟气排放过程（工况）自动监控系统技术规范[S]. 江苏省市场监督管理局. 2024-03-05.
• DB32／T+4681—2024 污染源视频监控系统建设规范[S]. 江苏省市场监督管理局. 2024-03-05.
• DB32／T+4822—2024 PID回路性能评估与优化实施技术规范[S]. 江苏省市场监督管理局. 2024-08-08.

软著

• 张登峰; 赵寿冬; 张泉灵; 喻果; 魏萃; 建筑用螺纹钢价格预测工业APPV1.0, 2023-04-25, 2023SR0503117.

• 张登峰; 丁祥龙; 常璐璐; 张泉灵; 喻果; 乙苯-苯乙烯精馏质量管控工业APPV1.0，2023-06-26, 2023SR0721959.

教改论文

• 喻果，江超，薄翠梅，李俊， 危化品应急管理多学科人才培养探索 [J]. 市场调查信息,2024(1):140-142.

• 喻果，江超，薄翠梅，张泉灵，《自控类专业写作》课程思政研究与实践[J]. 新时代教育, 2024(1):91-93.