2 citations · 4 across the 5 of their papers we have counts for
5 papers
CMIP X-MOS: Improving Climate Models with Extreme Model Output Statistics
Vsevolod Morozov, Artem Galliamov, Aleksandr Lukashevich +2
Climate models are essential for assessing the impact of greenhouse gas emissions on our changing climate and the resulting increase in the frequency and severity of natural disast…
Climate Change Impact on Agricultural Land Suitability: An Interpretable Machine Learning-Based Eurasia Case Study
Valeriy Shevchenko, Daria Taniushkina, Aleksander Lukashevich +7
The United Nations has identified improving food security and reducing hunger as essential components of its sustainable development goals. As of 2021, approximately 828 million pe…
GP CC-OPF: Gaussian Process based optimization tool for Chance-Constrained Optimal Power Flow
Mile Mitrovic, Ognjen Kundacina, Aleksandr Lukashevich +4
The Gaussian Process (GP) based Chance-Constrained Optimal Power Flow (CC-OPF) is an open-source Python code developed for solving economic dispatch (ED) problem in modern power gr…
Data-Driven Chance Constrained AC-OPF using Hybrid Sparse Gaussian Processes
Mile Mitrovic, Aleksandr Lukashevich, Petr Vorobev +3
The alternating current (AC) chance-constrained optimal power flow (CC-OPF) problem addresses the economic efficiency of electricity generation and delivery under generation uncert…
Data-Driven Stochastic AC-OPF using Gaussian Processes
Mile Mitrovic, Aleksandr Lukashevich, Petr Vorobev +4
In recent years, electricity generation has been responsible for more than a quarter of the greenhouse gas emissions in the US. Integrating a significant amount of renewables into…