Corrosion effect on inspection and replacement planning for a refinery plant. - Kyungjae Tak; Junghwan Kim 001 (Comput. Chem. Eng., 2018)

Techno-economic assessment of carbonate melt flue gas desulfurization process. - Juwon Lee; Hyungtae Cho; Il Moon; Igor Lubomirsky; Valery Kaplan; Junghwan Kim 001; Yuchan Ahn (Comput. Chem. Eng., 2021)

Cover: International Journal of Intelligent Systems, Volume 36 Issue 5 May 2021. - Hyukwon Kwon; Kwang Cheol Oh; Yeongryeol Choi; Yongchul G. Chung; Junghwan Kim 001 (Int. J. Intell. Syst., 2021)

Development and application of machine learning-based prediction model for distillation column. - Hyukwon Kwon; Kwang Cheol Oh; Yeongryeol Choi; Yongchul G. Chung; Junghwan Kim 001 (Int. J. Intell. Syst., 2021)

Time-series clustering approach for training data selection of a data-driven predictive model: Application to an industrial bio 2, 3-butanediol distillation process. - Yeongryeol Choi; Nahyeon An; Seokyoung Hong; Hyungtae Cho; Jongkoo Lim; In-Su Han; Il Moon; Junghwan Kim 001 (Comput. Chem. Eng., 2022)

Cover: International Journal of Intelligent Systems, Volume 37 Issue 6 June 2022. - Chonghyo Joo; Hyundo Park; Jongkoo Lim; Hyungtae Cho; Junghwan Kim 001 (Int. J. Intell. Syst., 2022)

Development of physical property prediction models for polypropylene composites with optimizing random forest hyperparameters. - Chonghyo Joo; Hyundo Park; Jongkoo Lim; Hyungtae Cho; Junghwan Kim 001 (Int. J. Intell. Syst., 2022)

Chemical Property-Guided Neural Networks for Naphtha Composition Prediction. - Chonghyo Joo; Jeongdong Kim; Hyungtae Cho; Jaewon Lee; Sungho Suh; Junghwan Kim 001 (INDIN, 2023)

Cluster-Based Multiobjective Particle Swarm Optimization and Application for Chemical Plants. - Seokyoung Hong; Jaewon Lee; Hyungtae Cho; Kyojin Jang; Junghwan Kim 001 (Int. J. Intell. Syst., 2023)

Multi-objective robust optimization of profit for a naphtha cracking furnace considering uncertainties in the feed composition. - Jeongdong Kim; Chonghyo Joo; Minsu Kim; Nahyeon An; Hyungtae Cho; Il Moon; Junghwan Kim 001 (Expert Syst. Appl., 2023)

A Dynamic Soft Sensor Based on Hybrid Neural Networks to Improve Early Off-spec Detection. - Seokyoung Hong; Nahyeon An; Hyungtae Cho; Jongkoo Lim; In-Su Han; Il Moon; Junghwan Kim 001 (Eng. Comput., 2023)

A novel graph-based missing values imputation method for industrial lubricant data. - Soohwan Jeong; Chonghyo Joo; Jongkoo Lim; Hyungtae Cho; Sungsu Lim; Junghwan Kim 001 (Comput. Ind., 2023)

pyAPEP: An all-in-one software package for the automated preparation of adsorption process simulations. - Seongbin Ga; Nahyeon An; Chonghyo Joo; Junghwan Kim 001 (Comput. Phys. Commun., 2023)

Correction to: A dynamic soft sensor based on hybrid neural networks to improve early off-spec detection. - Seokyoung Hong; Nahyeon An; Hyungtae Cho; Jongkoo Lim; In-Su Han; Il Moon; Junghwan Kim 001 (Eng. Comput., 2023)

Dual attention-based multi-step ahead prediction enhancement for monitoring systems in industrial processes. - Nahyeon An; Seokyoung Hong; Yurim Kim; Hyungtae Cho; Jongkoo Lim; Il Moon; Junghwan Kim 001 (Appl. Soft Comput., 2023)

Machine learning-based heat deflection temperature prediction and effect analysis in polypropylene composites using catboost and shapley additive explanations. - Chonghyo Joo; Hyundo Park; Jongkoo Lim; Hyungtae Cho; Junghwan Kim 001 (Eng. Appl. Artif. Intell., 2023)

Novel natural gradient boosting-based probabilistic prediction of physical properties for polypropylene-based composite data. - Hyundo Park; Chonghyo Joo; Jongkoo Lim; Junghwan Kim 001 (Eng. Appl. Artif. Intell., 2024)

Hyperparameter Optimization of the Machine Learning Model for Distillation Processes. - Kwang Cheol Oh; Hyukwon Kwon; Sun Yong Park; Seok Jun Kim; Junghwan Kim 001; Daehyun Kim (Int. J. Intell. Syst., 2024)

Novel inverse predictive system integrated with industrial lubricant information. - Minseong Kim; Chonghyo Joo; Jongkoo Lim; Seungho Yeom; Il Moon; Meng Qi; Junghwan Kim 001 (Eng. Appl. Artif. Intell., 2025)