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2020 – today
- 2024
[j7]Hyundo Park, Chonghyo Joo, Jongkoo Lim
, Junghwan Kim:
Novel natural gradient boosting-based probabilistic prediction of physical properties for polypropylene-based composite data. Eng. Appl. Artif. Intell. 135: 108864 (2024)- 2023
- [j6]Soohwan Jeong, Chonghyo Joo, Jongkoo Lim, Hyungtae Cho, Sungsu Lim, Junghwan Kim:
A novel graph-based missing values imputation method for industrial lubricant data. Comput. Ind. 150: 103937 (2023) - [j5]Seongbin Ga, Nahyeon An, Chonghyo Joo, Junghwan Kim:
pyAPEP: An all-in-one software package for the automated preparation of adsorption process simulations. Comput. Phys. Commun. 291: 108830 (2023) - [j4]Chonghyo Joo, Hyundo Park, Jongkoo Lim, Hyungtae Cho, Junghwan Kim:
Machine learning-based heat deflection temperature prediction and effect analysis in polypropylene composites using catboost and shapley additive explanations. Eng. Appl. Artif. Intell. 126: 106873 (2023) - [j3]Jeongdong Kim, Chonghyo Joo, Minsu Kim, Nahyeon An, Hyungtae Cho, Il Moon, Junghwan Kim:
Multi-objective robust optimization of profit for a naphtha cracking furnace considering uncertainties in the feed composition. Expert Syst. Appl. 216: 119464 (2023) - [c1]Chonghyo Joo, Jeongdong Kim, Hyungtae Cho, Jaewon Lee, Sungho Suh, Junghwan Kim:
Chemical Property-Guided Neural Networks for Naphtha Composition Prediction. INDIN 2023: 1-6 - [i1]Chonghyo Joo, Jeongdong Kim, Hyungtae Cho, Jaewon Lee, Sungho Suh, Junghwan Kim:
Chemical Property-Guided Neural Networks for Naphtha Composition Prediction. CoRR abs/2306.01391 (2023) - 2022
- [j2]Chonghyo Joo, Hyundo Park, Jongkoo Lim, Hyungtae Cho, Junghwan Kim:
Development of physical property prediction models for polypropylene composites with optimizing random forest hyperparameters. Int. J. Intell. Syst. 37(6): 3625-3653 (2022) - [j1]Chonghyo Joo, Hyundo Park, Jongkoo Lim, Hyungtae Cho, Junghwan Kim:
Cover: International Journal of Intelligent Systems, Volume 37 Issue 6 June 2022. Int. J. Intell. Syst. 37(6): i (2022)
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