Optimization of $CO_2$ vibrational kinetics modeling in the full state-to-state approach
V. I. Gorikhovskii, E. A. Nagnibeda

This publication is cited in the following articles:

1. Paola Lecca, “Guidelines to design the architecture of Artificial Neural Networks for application in physical chemistry”, J. Phys.: Conf. Ser., 3027:1 (2025), 012032  
2. Yu. N. Voroshilova, V. A. Istomin, O. V. Kunova, E. V. Kustova, E. A. Nagnibeda, M. A. Rydalevskaya, “Scientific School of Nonequilibrium Aeromechanics at St. Petersburg State University”, Vestnik St.Petersb. Univ.Math., 56:3 (2023), 289  
3. Yu. N. Voroshilova, V. A. Istomin, O. V. Kunova, E. V. Kustova, E. A. Nagnibeda, M. A. Rydalevskaya, “Nauchnaya shkola neravnovesnoi aeromekhaniki SPbGU”, Vestnik Sankt-Peterburgskogo universiteta. Matematika. Mekhanika. Astronomiya, 10:3 (2023), 406–456    
4. V. I. Gorikhovskii, E. V. Kustova, “Neural network approach in modelling vibrational kinetics of carbon dioxide”, Vestn. St. Petersbg. Univ., Math., 9:4 (2022), 434–442        
5. V I Gorikhovskii, T O Evdokimova, V A Poletansky, “Neural networks in solving differential equations”, J. Phys.: Conf. Ser., 2308:1 (2022), 012008