Nikolay O. Nikitin
Orcid: 0000-0002-6839-9957
According to our database1,
Nikolay O. Nikitin
authored at least 32 papers
between 2018 and 2024.
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Bibliography
2024
Integration of evolutionary automated machine learning with structural sensitivity analysis for composite pipelines.
Knowl. Based Syst., 2024
GOLEM: Flexible Evolutionary Design of Graph Representations of Physical and Digital Objects.
Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2024
Proceedings of the IEEE Congress on Evolutionary Computation, 2024
Proceedings of the IEEE Congress on Evolutionary Computation, 2024
2023
Eng. Appl. Artif. Intell., March, 2023
Automated machine learning approach for time series classification pipelines using evolutionary optimization.
Knowl. Based Syst., 2023
Integration Of Evolutionary Automated Machine Learning With Structural Sensitivity Analysis For Composite Pipelines.
CoRR, 2023
CoRR, 2023
Interpretable Structural Analysis for Evolutionary Generative Design of Coastal Breakwaters.
Proceedings of the Optimization, Learning Algorithms and Applications, 2023
Improvement of Computational Performance of Evolutionary AutoML in a Heterogeneous Environment.
Proceedings of the IEEE Congress on Evolutionary Computation, 2023
2022
Hybrid and automated machine learning approaches for oil fields development: The case study of Volve field, North Sea.
Comput. Geosci., 2022
Automated evolutionary approach for the design of composite machine learning pipelines.
Future Gener. Comput. Syst., 2022
Oil reservoir recovery factor assessment using Bayesian networks based on advanced approaches to analogues clustering.
CoRR, 2022
Surrogate-Assisted Evolutionary Generative Design Of Breakwaters Using Deep Convolutional Networks.
Proceedings of the IEEE Congress on Evolutionary Computation, 2022
Evolutionary Automated Machine Learning for Multi-Scale Decomposition and Forecasting of Sensor Time Series.
Proceedings of the IEEE Congress on Evolutionary Computation, 2022
2021
Towards Generative Design of Computationally Efficient Mathematical Models with Evolutionary Learning.
Entropy, 2021
Automated Data-Driven Approach for Gap Filling in the Time Series Using Evolutionary Learning.
Proceedings of the 16th International Conference on Soft Computing Models in Industrial and Environmental Applications, 2021
Model-Agnostic Multi-objective Approach for the Evolutionary Discovery of Mathematical Models.
Proceedings of the Optimization, Learning Algorithms and Applications, 2021
Oil and Gas Reservoirs Parameters Analysis Using Mixed Learning of Bayesian Networks.
Proceedings of the Computational Science - ICCS 2021, 2021
Proceedings of the GECCO '21: Genetic and Evolutionary Computation Conference, 2021
Proceedings of the IEEE Congress on Evolutionary Computation, 2021
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.
Remote. Sens., 2020
CoRR, 2020
Proceedings of the GECCO '20: Genetic and Evolutionary Computation Conference, 2020
2019
REBEC: Robust Evolutionary-based Calibration Approach for the Numerical Wind Wave Model.
CoRR, 2019
Proceedings of the Computational Science - ICCS 2019, 2019
Deadline-driven approach for multi-fidelity surrogate-assisted environmental model calibration: SWAN wind wave model case study.
Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2019
2018
CoRR, 2018
A Conceptual Approach to Complex Model Management with Generalized Modelling Patterns and Evolutionary Identification.
Complex., 2018
Proceedings of the Computational Science - ICCS 2018, 2018
Proceedings of the Computational Science - ICCS 2018, 2018
Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2018