Hvatov A., Sorokin S. On Unified Formulation of Floquet Propagator in Cartesian and Polar Coordinates. Mechanisms and Machine Science. 2023. Vol. 125. pp. 713-724.
Nikitin N.O., Revin I., Hvatov A., Vychuzhanin P., Kalyuzhnaya A.V. Hybrid and Automated Machine Learning Approaches for Oil Fields Development: the Case Study of Volve Field, North Sea. Computers and Geosciences. 2022. Vol. 161. pp. 105061.
Hvatov A. Data-Driven Approach for the Floquet Propagator Inverse Problem Solution. ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. 2022. pp. 3813-3817.
Hvatov A., Sorokin S.V. A simple example of the tunnelling effect in periodic elastic structures. European Journal of Mechanics - A/Solids. 2022. No. in press. pp. 104807.
Maslyaev M., Hvatov A. Solver-Based Fitness Function for the Data-Driven Evolutionary Discovery of Partial Differential Equations. IEEE Congress on Evolutionary Computation, CEC 2022. 2022. pp. 1-8.
Шахкян К.А., Литвинцева А.В., Титов Р.В., Хватов А.А. Искусcтвенный интеллект в науке и бизнесе: два полушария одного мозга. XIV Санкт-Петербургский конгресс "Профессиональное образование, наука и инновации в XXI веке": сборник материалов (СПб, 29ноября-1декабря 2022г.). 2022. С. 235-237.
Maslyaev M., Hvatov A., Kalyuzhnaya A.V. Partial differential equations discovery with EPDE framework: Application for real and synthetic data (R). Journal of Computational Science. 2021. Vol. 53. pp. 101345.
Hvatov A., Maslyaev M., Polonskaia I.S., Sarafanov M.I., Merezhnikov M., Nikitin N.O. Model-Agnostic Multi-objective Approach for the Evolutionary Discovery of Mathematical Models. Communications in Computer and Information Science. 2021. Vol. 1488. pp. 72-85.
Merezhnikov M., Hvatov A. Multi-objective closed-form algebraic expressions discovery approach application to the synthetic time-series generation. Procedia Computer Science. 2021. Vol. 193. pp. 285-294.
Kalyuzhnaya A.V., Nikitin N.O., Hvatov A., Maslyaev M., Yachmenkov M., Boukhanovsky A.V. Towards generative design of computationally efficient mathematical models with evolutionary learning. Entropy. 2021. Vol. 23. No. 1. pp. 28.
Maslyaev M., Hvatov A. Multi-Objective Discovery of PDE Systems Using Evolutionary Approach. IEEE Congress on Evolutionary Computation, CEC 2021. 2021. pp. 596-603.
Nikitin N.O., Hvatov A., Polonskaia I.S., Kalyuzhnaya A.V., Grigorev G., Wang X., Qian X. Generative design of microfluidic channel geometry using evolutionary approach. GECCO 2021 - Proceedings of the Genetic and Evolutionary Computation Conference Companion. 2021. pp. 59-60.
Быков Н.Ю., Хватов А.А., Калюжная А.В., Бухановский А.В. Метод восстановления моделей тепломассопереноса по пространственно-временным распределениям параметров. Письма в Журнал технической физики. 2021. Т. 47. № 24. С. 9-12.
Современные методы оптимизации с примерами на Python
Rezaei A., Carcaterra A., Sorokin S.V., Hvatov A., Mezzani F. Propagation of waves in nonlocal-periodic systems. Journal of Sound and Vibration. 2021. Vol. 506. pp. 116156.
Bykov N., Hvatov A., Kalyuzhnaya A.V., Boukhanovsky A.V. A method of generative model design based on irregular data in application to heat transfer problems. Journal of Physics: Conference Series. 2021. Vol. 1959. No. 1. pp. 012012.
Maslyaev M., Hvatov A., Kalyuzhnaya A.V. Discovery of the data-driven models of continuous metocean process in form of nonlinear ordinary differential equations. Procedia Computer Science. 2020. Vol. 178. pp. 18-26.
Merezhnikov M., Hvatov A. Closed-form algebraic expressions discovery using combined evolutionary optimization and sparse regression approach. Procedia Computer Science. 2020. Vol. 178. pp. 424-433.
Калюжная А.В., Никитин Н.О., Вычужанин П.В., Хватов А.А. Технологии прикладного искусcтвенного интеллекта в задачах численного моделирования процессов в океане. Комплексные исследования Мирового океана: материалы V Всероссийской научной конференции молодых ученых (Калининград, 18-22мая 2020г.). 2020. С. 81-82.
Hvatov A., Maslyaev M. The data-driven physical-based equations discovery using evolutionary approach. GECCO 2020 - Proceedings of the Genetic and Evolutionary Computation Conference Companion. 2020. pp. 129–130.
Maslyaev M., Hvatov A., Kalyuzhnaya A. Data-Driven Partial Differential Equations Discovery Approach for the Noised Multi-dimensional Data. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2020. Vol. 12138 LNCS. pp. 86-100.
Kaluzhnaya A.V., Nikitin N.O., Vychuzhanin P., Hvatov A., Boukhanovsky A.V. Automatic Evolutionary Learning of Composite Models With Knowledge Enrichment. GECCO 2020 - Proceedings of the Genetic and Evolutionary Computation Conference Companion. 2020. pp. 43-44.
Хватов А.А. Анализ бесконечной периодической структуры и ее конечной части с учетом слабой нелинейности. Ученые записки физического факультета МГУ. 2020. № 1. С. 2011201.
Hvatov A., Sorokin S.V. Analysis of periodicity-induced attenuation effect in a nonlinear waveguide by means of the method of polynomial system resultants. Mechanics Research Communications. 2020. Vol. 103. pp. 103476.
Nikitin N.O., Deeva I., Vychuzhanin P., Kalyuzhnaya A.V., Hvatov A., Kovalchuk S.V. Deadline-driven approach for multi-fidelity surrogate-assisted environmental model calibration: SWAN wind wave model case study. GECCO 2019 - Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion. 2019. pp. 1583-1591.
Hvatov A., Sorokin S.V. Floquet theory analysis of a weakly non-linear periodic structure. COMPDYN Proceedings. 2019. Vol. 2. pp. 3457-3464.
Обнаружение аномалий в результатах гидрометеорологического моделирования с использованием сверточных нейронных сетей
Maslyaev M., Hvatov A. Discovery of the data-driven differential equation-based models of continuous metocean process. Procedia Computer Science. 2019. Vol. 156. pp. 367-376.
Hvatov A. The symmetrical cell eigenfrequency method for periodic structure stop-band definition. Vibroengineering Procedia. 2019. Vol. 25. pp. 100-105.
Khvatov A.A., Nikitin N., Kaluzhnaya A.V., Kosukhin S.S. Adaptation of NEMO-LIM3 model for multigrid high-resolution Arctic simulation. Ocean Modelling. 2019. Vol. 141. pp. 101427.
Maslyaev M., Hvatov A., Kalyuzhnaya A.V. Data-driven partial derivative equations discovery with evolutionary approach. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2019. Vol. 11540 LNCS. pp. 635-641.
Hvatov A., Sorokin S. Assessment of reduced-order models in analysis of Floquet modes in an infinite periodic elastic layer. Journal of Sound and Vibration. 2019. Vol. 440. pp. 332-345.
Hvatov A., Sorokin S. On application of the Floquet theory for radially periodic membranes and plates. Journal of Sound and Vibration. 2018. Vol. 414. pp. 15-30.
Vychuzhanin P., Hvatov A., Kalyuzhnaya A.V. Anomalies Detection in Metocean Simulation Results Using Convolutional Neural Networks. Procedia Computer Science. 2018. Vol. 136. pp. 321-330.
Хватов А.А. Теория Флоке в анализе виброизоляции. Ученые записки физического факультета МГУ. 2017. № 5. С. 1751413.
Hvatov A., Sorokin S. Cylindrical waves in structures periodic in polar coordinates. 6th International Conference on Computational Methods in Structural Dynamics and Earthquake Engineering, COMPDYN 2017. 2017. pp. 509-517.
Hvatov A., Sorokin S. Free vibrations of finite periodic structures in pass-and stop-bands of the counterpart infinite waveguides. Journal of Sound and Vibration. 2015. Vol. 347. pp. 200-217.
Хватов А.А. Analysis of eigenfrequencies of finite periodic structures in view of location of frequency pas-and stop-bands. Proceedings of 20th International Congress on Sound and Vibration. 2013. pp. 1-8.
Российская Федерация, Санкт-Петербург
Российская Федерация, Санкт-Петербург