Simulation-based collaborative decision support for surge floods prevention in St. Petersburg. - Sergey V. Ivanov; Sergey S. Kosukhin; Anna V. Kaluzhnaya; Alexander Boukhanovsky (J. Comput. Sci., 2012)

Erratum to "Simulation-based collaborative decision support for surge floods prevention in St. Petersburg" [J. Comput. Sciience 3 (2012) 450-455]. - Sergey V. Ivanov; Sergey S. Kosukhin; Anna V. Kaluzhnaya; Alexander Boukhanovsky (J. Comput. Sci., 2013)

Problem Solving Environment for Development and Maintenance of St. Petersburg's Flood Warning System. - Sergey S. Kosukhin; Anna V. Kalyuzhnaya; Denis A. Nasonov (ICCS, 2014)

Computational Uncertainty Management for Coastal Flood Prevention System. - Anna V. Kalyuzhnaya; Alexander Boukhanovsky (ICCS, 2015)

Synthetic storms reconstruction for coastal floods risks assessment. - Anna V. Kalyuzhnaya; Alexander A. Visheratin; Alexey Dudko; Denis A. Nasonov; Alexander V. Boukhanovsky (J. Comput. Sci., 2015)

Data Quality Control for St. Petersburg Flood Warning System. - Jose Luis Araya-Lopez; Anna V. Kalyuzhnaya; Sergey S. Kosukhin; Sergey V. Ivanov; Alexander Boukhanovsky (ICCS, 2016)

Uncertainty quantification and sensitivity analysis applied to the wind wave model SWAN. - Anna Nikishova; Anna V. Kaluzhnaya; Alexander Boukhanovsky; Alfons G. Hoekstra (Environ. Model. Softw., 2017)

Towards management of complex modeling through a hybrid evolutionary identification. - Sergey V. Kovalchuk; Oleg G. Metsker; Anastasia A. Funkner; Ilia O. Kisliakovskii; Nikolay O. Nikitin; Anna V. Kalyuzhnaya; Danila A. Vaganov; Klavdiya O. Bochenina (GECCO (Companion), 2018)

Precedent-Based Approach for the Identification of Deviant Behavior in Social Media. - Anna V. Kalyuzhnaya; Nikolay O. Nikitin; Nikolay Butakov; Denis A. Nasonov (ICCS (3), 2018)

Evolutionary Ensemble Approach for Behavioral Credit Scoring. - Nikolay O. Nikitin; Anna V. Kalyuzhnaya; Klavdiya Bochenina; Alexander A. Kudryashov; Amir Uteuov; Ivan Derevitskii; Alexander V. Boukhanovsky (ICCS (3), 2018)

A Conceptual Approach to Complex Model Management with Generalized Modelling Patterns and Evolutionary Identification. - Sergey V. Kovalchuk; Oleg G. Metsker; Anastasia A. Funkner; Ilia O. Kisliakovskii; Nikolay O. Nikitin; Anna V. Kalyuzhnaya; Danila A. Vaganov; Klavdiya O. Bochenina (Complex., 2018)

Adaptation of NEMO-LIM3 model for multigrid high resolution Arctic simulation. - Alexander Hvatov; Nikolay O. Nikitin; Anna V. Kalyuzhnaya; Sergey S. Kosukhin (CoRR, 2018)

Towards a scenario-based solution for extreme metocean event simulation applying urgent computing. - Anna V. Kalyuzhnaya; Denis A. Nasonov; Sergey V. Ivanov; Sergey S. Kosukhin; Alexander V. Boukhanovsky (Future Gener. Comput. Syst., 2018)

Deadline-driven approach for multi-fidelity surrogate-assisted environmental model calibration: SWAN wind wave model case study. - Nikolay O. Nikitin; Pavel Vychuzhanin; Alexander Hvatov; Irina Deeva; Anna V. Kalyuzhnaya; Sergey V. Kovalchuk (GECCO (Companion), 2019)

Data-Driven Partial Derivative Equations Discovery with Evolutionary Approach. - Mikhail Maslyaev; Alexander Hvatov; Anna V. Kalyuzhnaya (ICCS (5), 2019)

Robust Ensemble-Based Evolutionary Calibration of the Numerical Wind Wave Model. - Pavel Vychuzhanin; Nikolay O. Nikitin; Anna V. Kalyuzhnaya (ICCS (1), 2019)

Data-driven PDE discovery with evolutionary approach. - Michail Maslyaev; Alexander Hvatov; Anna V. Kalyuzhnaya (CoRR, 2019)

REBEC: Robust Evolutionary-based Calibration Approach for the Numerical Wind Wave Model. - Pavel Vychuzhanin; Nikolay O. Nikitin; Anna V. Kalyuzhnaya (CoRR, 2019)

Automatic evolutionary learning of composite models with knowledge enrichment. - Anna V. Kalyuzhnaya; Nikolay O. Nikitin; Pavel Vychuzhanin; Alexander Hvatov; Alexander Boukhanovsky (GECCO Companion, 2020)

Bayesian Networks-based personal data synthesis. - Irina Deeva; Petr D. Andriushchenko; Anna V. Kalyuzhnaya; Alexander V. Boukhanovsky (GOODTECHS, 2020)

Data-Driven Partial Differential Equations Discovery Approach for the Noised Multi-dimensional Data. - Mikhail Maslyaev; Alexander Hvatov; Anna V. Kalyuzhnaya (ICCS (2), 2020)

The multi-objective optimisation of breakwaters using evolutionary approach. - Nikolay O. Nikitin; Iana S. Polonskaia; Anna V. Kalyuzhnaya; Alexander V. Boukhanovsky (CoRR, 2020)

A Machine Learning Approach for Remote Sensing Data Gap-Filling with Open-Source Implementation: An Example Regarding Land Surface Temperature, Surface Albedo and NDVI. - Mikhail Sarafanov; Eduard Kazakov; Nikolay O. Nikitin; Anna V. Kalyuzhnaya (Remote. Sens., 2020)

Multi-Objective Evolutionary Design of Composite Data-Driven Models. - Iana S. Polonskaia; Nikolay O. Nikitin; Ilia Revin; Pavel Vychuzhanin; Anna V. Kalyuzhnaya (CEC, 2021)

Generative design of microfluidic channel geometry using evolutionary approach. - Nikolay O. Nikitin; Alexander Hvatov; Iana S. Polonskaia; Anna V. Kalyuzhnaya; Georgii V. Grigorev; Xiaohao Wang; Xiang Qian (GECCO Companion, 2021)

Oil and Gas Reservoirs Parameters Analysis Using Mixed Learning of Bayesian Networks. - Irina Deeva; Anna Bubnova; Petr D. Andriushchenko; Anton Voskresenskiy; Nikita V. Bukhanov; Nikolay O. Nikitin; Anna V. Kalyuzhnaya (ICCS (1), 2021)

A Multimodal Approach to Synthetic Personal Data Generation with Mixed Modelling: Bayesian Networks, GAN's and Classification Models. - Irina Deeva; Andrey Mossyayev; Anna V. Kalyuzhnaya (MobiQuitous, 2021)

Automated Data-Driven Approach for Gap Filling in the Time Series Using Evolutionary Learning. - Mikhail Sarafanov; Nikolay O. Nikitin; Anna V. Kalyuzhnaya (SOCO, 2021)

MIxBN: library for learning Bayesian networks from mixed data. - Anna V. Bubnova; Irina Deeva; Anna V. Kalyuzhnaya (CoRR, 2021)

Towards Generative Design of Computationally Efficient Mathematical Models with Evolutionary Learning. - Anna V. Kalyuzhnaya; Nikolay O. Nikitin; Alexander Hvatov; Mikhail Maslyaev; Mikhail Yachmenkov; Alexander Boukhanovsky (Entropy, 2021)

Partial differential equations discovery with EPDE framework: Application for real and synthetic data. - Mikhail Maslyaev; Alexander Hvatov; Anna V. Kalyuzhnaya (J. Comput. Sci., 2021)

Surrogate-Assisted Evolutionary Generative Design Of Breakwaters Using Deep Convolutional Networks. - Nikita O. Starodubcev; Nikolay O. Nikitin; Anna V. Kalyuzhnaya (CEC, 2022)

Oil reservoir recovery factor assessment using Bayesian networks based on advanced approaches to analogues clustering. - Petr D. Andriushchenko; Irina Deeva; Anna Bubnova; Anton Voskresenskiy; Nikita V. Bukhanov; Nikolay O. Nikitin; Anna V. Kalyuzhnaya (CoRR, 2022)

Automated evolutionary approach for the design of composite machine learning pipelines. - Nikolay O. Nikitin; Pavel Vychuzhanin; Mikhail Sarafanov; Iana S. Polonskaia; Ilia Revin; Irina V. Barabanova; Gleb Maximov; Anna V. Kalyuzhnaya; Alexander Boukhanovsky (Future Gener. Comput. Syst., 2022)

Hybrid and automated machine learning approaches for oil fields development: The case study of Volve field, North Sea. - Nikolay O. Nikitin; Ilia Revin; Alexander Hvatov; Pavel Vychuzhanin; Anna V. Kalyuzhnaya (Comput. Geosci., 2022)

A Multi-Contractor Approach for MLRCPSP with the Graph Structure Optimization. - Anastasiia Filatova; Mikhail V. Kovalchuk; Stanislav Batalenkov; Aleksander Voskresenskiy; Irina Deeva; Anna V. Kaluzhnaya; Aleksei Shpilman; Natalia Kondrashova; Maxim Dudnichenko; Denis A. Nasonov (CEC, 2023)

Integration Of Evolutionary Automated Machine Learning With Structural Sensitivity Analysis For Composite Pipelines. - Nikolay O. Nikitin; Maiia Pinchuk; Valerii Pokrovskii; Peter Shevchenko; Andrey Getmanov; Yaroslav Aksenkin; Ilia Revin; Andrey Stebenkov; Ekaterina Poslavskaya; Anna V. Kalyuzhnaya (CoRR, 2023)

Assessing the Mass Transfer Coefficient in Jet Bioreactors with Classical Computer Vision Methods and Neural Networks Algorithms. - Irina Nizovtseva; Vladimir Palmin; Ivan Simkin; Ilya Starodumov; Pavel Mikushin; Alexander Nozik; Timur Hamitov; Sergey Ivanov; Sergey Vikharev; Alexei Zinovev; Vladislav Svitich; Matvey Mogilev; et al. (Algorithms, 2023)

Generative design of physical objects using modular framework. - Nikita O. Starodubcev; Nikolay O. Nikitin; Elizaveta A. Andronova; Konstantin G. Gavaza; Denis O. Sidorenko; Anna V. Kalyuzhnaya (Eng. Appl. Artif. Intell., 2023)

GOLEM: Flexible Evolutionary Design of Graph Representations of Physical and Digital Objects. - Maiia Pinchuk; Grigorii Kirgizov; Lyubov Yamshchikova; Nikolay O. Nikitin; Irina Deeva; Karine Shakhkyan; Ivan I. Borisov; Kirill Zharkov; Anna V. Kalyuzhnaya (GECCO Companion, 2024)

Evolutionary Optimization for Inverse Problem in Engineering: The Case Study of Defects Shape Reconstruction. - Gleb V. Solovev; Alexander Hvatov; Oleg Petrov; Anna V. Kalyuzhnaya; Alexandra Klimova; Nikolay O. Nikitin (OL2A (2), 2024)

Integration of evolutionary automated machine learning with structural sensitivity analysis for composite pipelines. - Nikolay O. Nikitin; Maiia Pinchuk; Valerii Pokrovskii; Peter Shevchenko; Andrey Getmanov; Yaroslav Aksenkin; Ilia Revin; Andrey Stebenkov; Vladimir Latypov; Ekaterina Poslavskaya; Anna V. Kalyuzhnaya (Knowl. Based Syst., 2024)