Issue
Total 10 articles [ 키워드: Machine Learning ]
No. Article
1 Korean Journal of Chemical Engineering, 40 (12), pp.2941-2956 (2023)
Application of machine learning and genetic algorithms to the prediction and optimization of biodiesel yield from waste cooking oil
Aqueel Ahmad, Ashok Kumar Yadav, Achhaibar Singh
2 Korean Journal of Chemical Engineering, 40 (9), pp.2091-2101 (2023)
An LSTM model with optimal feature selection for predictions of tensile behavior and tensile failure of polymer matrix composites
Jaewook Lee, Nagyeong Lee, Jinkyung Son, et al.
3 Korean Journal of Chemical Engineering, 40 (9), pp.2119-2127 (2023)
Physics-informed neural networks for learning fluid flows with symmetry
Younghyeon Kim, Hyungyeol Kwak, Jaewook Nam
4 Korean Journal of Chemical Engineering, 40 (8), pp.1850-1862 (2023)
Feature construction for on-board early prediction of electric vehicle battery cycle life
Junseop Shin, Yeonsoo Kim, Jong Min Lee
5 Korean Journal of Chemical Engineering, 40 (5), pp.1023-1036 (2023)
Soft sensor development based on just-in-time learning and dynamic time warping for multi-grade processes
Min Jun Song, Sung Hyun Ju, Jong Min Lee
6 Korean Journal of Chemical Engineering, 40 (3), pp.539-547 (2023)
Data-driven designs and multi-scale simulations of enhanced ion transport in low-temperature operation for lithium-ion batteries
Chang HJ, Park YJ, Kim JH, et al.
7 Korean Journal of Chemical Engineering, 40 (2), pp.276-285 (2023)
Recent development of machine learning models for the prediction of drug-drug interactions
Hong EJ, Jeon JH, Kim HU
8 Korean Journal of Chemical Engineering, 39 (4), pp.811-820 (2022)
New frontiers of quantum computing in chemical engineering
Ajagekar A, You F
9 Korean Journal of Chemical Engineering, 38 (10), pp.1971-1982 (2021)
Machine learning-based discovery of molecules, crystals, and composites: A perspective review
Lee SW, Byun HE, Cheon MJ, et al.
10 Korean Journal of Chemical Engineering, 38 (6), pp.1117-1128 (2021)
Recent progress on Al distribution over zeolite frameworks:Linking theories and experiments
Kwak SJ, Kim HS, Park NJ, et al.