Vladyslav Nechakhin

Orcid: 0000-0003-0146-1207

According to our database1, Vladyslav Nechakhin authored at least 10 papers between 2020 and 2026.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
KGEval: Evaluating Scientific Knowledge Graphs with Large Language Models.
Inf., 2026

2024
Evaluating Large Language Models for Structured Science Summarization in the Open Research Knowledge Graph.
Inf., June, 2024

Enhancing solar panel efficiency with LSTM-based MPPT controllers.
Proceedings of the Modern Machine Learning Technologies Workshop (MoMLeT 2024), 2024

Approach to Identification of Anomalous Values in Analysis Tasks and Data Pre-processing.
Proceedings of the Lecture Notes in Data Engineering, Computational Intelligence, and Decision-Making, Volume 2, 2024

2023
Similar Papers Recommendation for Research Comparisons.
Proceedings of the Joint Workshop Proceedings of the 5th International Workshop on A Semantic Data Space For Transport (Sem4Tra) and 2nd NLP4KGC: Natural Language Processing for Knowledge Graph Construction co-located with the 19th International Conference on Semantic Systems (SEMANTiCS 2023), 2023

Hyperparameter Optimization of LSTM MPPT Controller for Solar Power Plants.
Proceedings of the 18th IEEE International Conference on Computer Science and Information Technologies, 2023

Building a Fuel Measurement System Model based on Colored Petri Nets.
Proceedings of the 18th IEEE International Conference on Computer Science and Information Technologies, 2023

2021
Modeling an Intelligent Solar Power Plant Control System Using Colored Petri Nets.
Proceedings of the 2021 11th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS), 2021

2020
Solar Power Control System based on Machine Learning Methods.
Proceedings of the IEEE 15th International Conference on Computer Sciences and Information Technologies, 2020

Hybrid Power Plant Control System Based on Machine Learning Methods.
Proceedings of the Advances in Intelligent Systems and Computing V, 2020


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