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ORCIDNikolay O. Nikitin
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2020 – today
- 2023
[j6]Nikita O. Starodubcev, Nikolay O. Nikitin
, Elizaveta A. Andronova, Konstantin G. Gavaza, Denis O. Sidorenko, Anna V. Kalyuzhnaya:
Generative design of physical objects using modular framework. Eng. Appl. Artif. Intell. 119: 105715 (2023)- [i14]Nikolay O. Nikitin, Sergey Teryoshkin, Valerii Pokrovskii, Sergey Pakulin, Denis A. Nasonov:
Improvement of Computational Performance of Evolutionary AutoML in a Heterogeneous Environment. CoRR abs/2301.05102 (2023) - 2022
- [j5]Nikolay O. Nikitin, Pavel Vychuzhanin, Mikhail Sarafanov, Iana S. Polonskaia, Ilia Revin, Irina V. Barabanova, Gleb Maximov, Anna V. Kalyuzhnaya, Alexander Boukhanovsky:
Automated evolutionary approach for the design of composite machine learning pipelines. Future Gener. Comput. Syst. 127: 109-125 (2022) - [j4]Nikolay O. Nikitin, Ilia Revin, Alexander Hvatov, Pavel Vychuzhanin, Anna V. Kalyuzhnaya:
Hybrid and automated machine learning approaches for oil fields development: The case study of Volve field, North Sea. Comput. Geosci. 161: 105061 (2022) - [c13]Mikhail Sarafanov, Valerii Pokrovskii, Nikolay O. Nikitin:
Evolutionary Automated Machine Learning for Multi-Scale Decomposition and Forecasting of Sensor Time Series. CEC 2022: 1-8 - [c12]Nikita O. Starodubcev, Nikolay O. Nikitin, Anna V. Kalyuzhnaya:
Surrogate-Assisted Evolutionary Generative Design Of Breakwaters Using Deep Convolutional Networks. CEC 2022: 1-8 - [i13]Petr D. Andriushchenko, Irina Deeva, Anna Bubnova, Anton Voskresenskiy, Nikita V. Bukhanov, Nikolay O. Nikitin, Anna V. Kalyuzhnaya:
Oil reservoir recovery factor assessment using Bayesian networks based on advanced approaches to analogues clustering. CoRR abs/2204.00413 (2022) - [i12]Nikita O. Starodubcev, Nikolay O. Nikitin, Anna V. Kalyuzhnaya:
Surrogate-Assisted Evolutionary Generative Design Of Breakwaters Using Deep Convolutional Networks. CoRR abs/2204.03400 (2022) - [i11]Nikita O. Starodubcev, Nikolay O. Nikitin, Konstantin G. Gavaza, Elizaveta A. Andronova, Denis O. Sidorenko, Anna V. Kalyuzhnaya:
Generative Design of Physical Objects using Modular Framework. CoRR abs/2207.14621 (2022) - 2021
- [j3]Anna V. Kalyuzhnaya, Nikolay O. Nikitin, Alexander Hvatov, Mikhail Maslyaev, Mikhail Yachmenkov, Alexander Boukhanovsky:
Towards Generative Design of Computationally Efficient Mathematical Models with Evolutionary Learning. Entropy 23(1): 28 (2021) - [c11]Iana S. Polonskaia, Nikolay O. Nikitin, Ilia Revin, Pavel Vychuzhanin, Anna V. Kalyuzhnaya:
Multi-Objective Evolutionary Design of Composite Data-Driven Models. CEC 2021: 926-933 - [c10]Nikolay O. Nikitin, Alexander Hvatov, Iana S. Polonskaia, Anna V. Kalyuzhnaya, Georgii V. Grigorev, Xiaohao Wang, Xiang Qian:
Generative design of microfluidic channel geometry using evolutionary approach. GECCO Companion 2021: 59-60 - [c9]Irina Deeva, Anna Bubnova, Petr D. Andriushchenko, Anton Voskresenskiy, Nikita V. Bukhanov, Nikolay O. Nikitin, Anna V. Kalyuzhnaya:
Oil and Gas Reservoirs Parameters Analysis Using Mixed Learning of Bayesian Networks. ICCS (1) 2021: 394-407 - [c8]Alexander Hvatov, Mikhail Maslyaev, Iana S. Polonskaya, Mikhail Sarafanov, Mark Merezhnikov, Nikolay O. Nikitin:
Model-Agnostic Multi-objective Approach for the Evolutionary Discovery of Mathematical Models. OL2A 2021: 72-85 - [c7]Mikhail Sarafanov, Nikolay O. Nikitin, Anna V. Kalyuzhnaya:
Automated Data-Driven Approach for Gap Filling in the Time Series Using Evolutionary Learning. SOCO 2021: 633-642 - [i10]Mikhail Sarafanov, Nikolay O. Nikitin, Anna V. Kalyuzhnaya:
Automated data-driven approach for gap filling in the time series using evolutionary learning. CoRR abs/2103.01124 (2021) - [i9]Iana S. Polonskaia, Nikolay O. Nikitin, Ilia Revin, Pavel Vychuzhanin, Anna V. Kalyuzhnaya:
Multi-Objective Evolutionary Design of Composite Data-Driven Models. CoRR abs/2103.01301 (2021) - [i8]Irina Deeva, Anna Bubnova, Petr D. Andriushchenko, Anton Voskresenskiy, Nikita V. Bukhanov, Nikolay O. Nikitin, Anna V. Kalyuzhnaya:
Oil and Gas Reservoirs Parameters Analysis Using Mixed Learning of Bayesian Networks. CoRR abs/2103.01804 (2021) - [i7]Nikolay O. Nikitin, Ilia Revin, Alexander Hvatov, Pavel Vychuzhanin, Anna V. Kalyuzhnaya:
Hybrid and Automated Machine Learning Approaches for Oil Fields Development: the Case Study of Volve Field, North Sea. CoRR abs/2103.02598 (2021) - [i6]Nikolay O. Nikitin, Pavel Vychuzhanin, Mikhail Sarafanov, Iana S. Polonskaia, Ilia Revin, Irina V. Barabanova, Gleb Maximov, Anna V. Kalyuzhnaya, Alexander Boukhanovsky:
Automated Evolutionary Approach for the Design of Composite Machine Learning Pipelines. CoRR abs/2106.15397 (2021) - [i5]Alexander Hvatov, Mikhail Maslyaev, Iana S. Polonskaya, Mikhail Sarafanov, Mark Merezhnikov, Nikolay O. Nikitin:
Model-agnostic multi-objective approach for the evolutionary discovery of mathematical models. CoRR abs/2107.03146 (2021) - 2020
- [j2]Mikhail Sarafanov, Eduard Kazakov, Nikolay O. Nikitin, Anna V. Kalyuzhnaya:
A Machine Learning Approach for Remote Sensing Data Gap-Filling with Open-Source Implementation: An Example Regarding Land Surface Temperature, Surface Albedo and NDVI. Remote. Sens. 12(23): 3865 (2020) - [c6]Anna V. Kalyuzhnaya, Nikolay O. Nikitin, Pavel Vychuzhanin, Alexander Hvatov, Alexander Boukhanovsky:
Automatic evolutionary learning of composite models with knowledge enrichment. GECCO Companion 2020: 43-44 - [i4]Nikolay O. Nikitin, Iana S. Polonskaia, Anna V. Kalyuzhnaya, Alexander V. Boukhanovsky:
The multi-objective optimisation of breakwaters using evolutionary approach. CoRR abs/2004.03010 (2020)
2010 – 2019
- 2019
- [c5]Nikolay O. Nikitin, Pavel Vychuzhanin, Alexander Hvatov, Irina Deeva, Anna V. Kalyuzhnaya, Sergey V. Kovalchuk:
Deadline-driven approach for multi-fidelity surrogate-assisted environmental model calibration: SWAN wind wave model case study. GECCO (Companion) 2019: 1583-1591 - [c4]Pavel Vychuzhanin, Nikolay O. Nikitin, Anna V. Kalyuzhnaya:
Robust Ensemble-Based Evolutionary Calibration of the Numerical Wind Wave Model. ICCS (1) 2019: 614-627 - [i3]Pavel Vychuzhanin, Nikolay O. Nikitin, Anna V. Kalyuzhnaya:
REBEC: Robust Evolutionary-based Calibration Approach for the Numerical Wind Wave Model. CoRR abs/1906.08587 (2019) - 2018
- [j1]Sergey V. Kovalchuk, Oleg G. Metsker, Anastasia A. Funkner, Ilia O. Kisliakovskii, Nikolay O. Nikitin, Anna V. Kalyuzhnaya, Danila A. Vaganov, Klavdiya O. Bochenina:
A Conceptual Approach to Complex Model Management with Generalized Modelling Patterns and Evolutionary Identification. Complex. 2018: 5870987:1-5870987:15 (2018) - [c3]Sergey V. Kovalchuk, Oleg G. Metsker, Anastasia A. Funkner, Ilia O. Kisliakovskii, Nikolay O. Nikitin, Anna V. Kalyuzhnaya, Danila A. Vaganov, Klavdiya O. Bochenina:
Towards management of complex modeling through a hybrid evolutionary identification. GECCO (Companion) 2018: 255-256 - [c2]Nikolay O. Nikitin, Anna V. Kalyuzhnaya, Klavdiya Bochenina, Alexander A. Kudryashov, Amir Uteuov, Ivan Derevitskii, Alexander V. Boukhanovsky:
Evolutionary Ensemble Approach for Behavioral Credit Scoring. ICCS (3) 2018: 825-831 - [c1]Anna V. Kalyuzhnaya, Nikolay O. Nikitin, Nikolay Butakov, Denis A. Nasonov:
Precedent-Based Approach for the Identification of Deviant Behavior in Social Media. ICCS (3) 2018: 846-852 - [i2]Sergey V. Kovalchuk, Oleg G. Metsker, Anastasia A. Funkner, Ilia O. Kisliakovskii, Nikolay O. Nikitin, Anna V. Kalyuzhnaya, Danila A. Vaganov, Klavdiya O. Bochenina:
A Conceptual Approach to Complex Model Management with Generalized Modelling Patterns and Evolutionary Identification. CoRR abs/1809.04656 (2018) - [i1]Alexander Hvatov, Nikolay O. Nikitin, Anna V. Kalyuzhnaya, Sergey S. Kosukhin:
Adaptation of NEMO-LIM3 model for multigrid high resolution Arctic simulation. CoRR abs/1810.03657 (2018)
Coauthor Index
aka: Anna V. Kalyuzhnaya
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