2025-02-22T10:22:10-05:00 DEBUG: VuFindSearch\Backend\Solr\Connector: Query fl=%2A&wt=json&json.nl=arrarr&q=id%3A%22veorgua-article-455%22&qt=morelikethis&rows=5
2025-02-22T10:22:10-05:00 DEBUG: VuFindSearch\Backend\Solr\Connector: => GET http://localhost:8983/solr/biblio/select?fl=%2A&wt=json&json.nl=arrarr&q=id%3A%22veorgua-article-455%22&qt=morelikethis&rows=5
2025-02-22T10:22:10-05:00 DEBUG: VuFindSearch\Backend\Solr\Connector: <= 200 OK
2025-02-22T10:22:10-05:00 DEBUG: Deserialized SOLR response
DETERMINATION OF NETWORK TRAFFIC ANOMALIES IN A DISTRIBUTED COMPUTER SYSTEM WITH ENERGY FACILITIES

DETERMINATION OF NETWORK TRAFFIC ANOMALIES IN A DISTRIBUTED COMPUTER SYSTEM WITH ENERGY FACILITIES

The paper presents research, the purpose of which is to define a machine learning model for express analysis of network traffic in a distributed computer system for managing decentralized generation facilities based on renewable energy. The available tools for monitoring processes in the computer ne...

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Bibliographic Details
Main Authors: Shapovalova , S., Matіakh , S., Titov , V.
Format: Article
Language:English
Published: Institute of Renewable Energy National Academy of Sciences of Ukraine 2024
Subjects:
renewable energy
energy decentralization
MLP
RNN
LSTM
KNN
Logistic Regression
Decision Tree
GBM.
Online Access:https://ve.org.ua/index.php/journal/article/view/455
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https://ve.org.ua/index.php/journal/article/view/455

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