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07/29/2022
Generative Design of Physical Objects using Modular Framework
In recent years generative design techniques have become firmly establis...
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04/07/2022
Surrogate-Assisted Evolutionary Generative Design Of Breakwaters Using Deep Convolutional Networks
In the paper, a multi-objective evolutionary surrogate-assisted approach...
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06/26/2021
Automated Evolutionary Approach for the Design of Composite Machine Learning Pipelines
The effectiveness of the machine learning methods for real-world tasks d...
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06/24/2021
MIxBN: library for learning Bayesian networks from mixed data
This paper describes a new library for learning Bayesian networks from d...
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03/03/2021
Hybrid and Automated Machine Learning Approaches for Oil Fields Development: the Case Study of Volve Field, North Sea
The paper describes the usage of intelligent approaches for field develo...
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03/02/2021
Oil and Gas Reservoirs Parameters Analysis Using Mixed Learning of Bayesian Networks
In this paper, a multipurpose Bayesian-based method for data analysis, c...
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03/01/2021
Multi-Objective Evolutionary Design of Composite Data-Driven Models
In this paper, a multi-objective approach for the design of composite da...
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03/01/2021
Automated data-driven approach for gap filling in the time series using evolutionary learning
Time series analysis is widely used in various fields of science and ind...
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04/06/2020
The multi-objective optimisation of breakwaters using evolutionary approach
In engineering practice, it is often necessary to increase the effective...
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10/08/2018
Adaptation of NEMO-LIM3 model for multigrid high resolution Arctic simulation
Arctic ocean modelling is a complex, computationally-intensive task that...
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09/12/2018
