The Use of Machine Learning in Situational Management in Relation to the Tasks of the Power Industry
The article discusses the application possibilities of machine learning methods (artificial neural networks (ANN) and genetic algorithms (GA) to form management actions when applying the concept of situational management for intelligent support of strategic decision-making on the development of ener...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2019-01-01
|
| Series: | EPJ Web of Conferences |
| Subjects: | |
| Online Access: | https://www.epj-conferences.org/articles/epjconf/pdf/2019/22/epjconf_freps18_01010.pdf |
| _version_ | 1818721374303158272 |
|---|---|
| author | Massel Lyudmila V. Gerget Olga M. Massel Aleksei G. Mamedov Timur G. |
| author_facet | Massel Lyudmila V. Gerget Olga M. Massel Aleksei G. Mamedov Timur G. |
| author_sort | Massel Lyudmila V. |
| collection | DOAJ |
| description | The article discusses the application possibilities of machine learning methods (artificial neural networks (ANN) and genetic algorithms (GA) to form management actions when applying the concept of situational management for intelligent support of strategic decision-making on the development of energy. At the first stage, the application of ANN to classify extreme situations in the energy sector, to select the most effective management actions (preventive measures) in order to prevent a critical situation from developing into an emergency. Genetic algorithms are proposed to be used to determine the weighting coefficients for training ANN. An algorithm for constructing a classifier based on a neural network and a demonstration task using data on generation and consumption of the United Electric Power System of Siberia are presented. |
| first_indexed | 2024-12-17T20:37:43Z |
| format | Article |
| id | doaj.art-2e0bb6255e3543c7b04184f8b1a61412 |
| institution | Directory Open Access Journal |
| issn | 2100-014X |
| language | English |
| last_indexed | 2024-12-17T20:37:43Z |
| publishDate | 2019-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | EPJ Web of Conferences |
| spelling | doaj.art-2e0bb6255e3543c7b04184f8b1a614122022-12-21T21:33:24ZengEDP SciencesEPJ Web of Conferences2100-014X2019-01-012170101010.1051/epjconf/201921701010epjconf_freps18_01010The Use of Machine Learning in Situational Management in Relation to the Tasks of the Power IndustryMassel Lyudmila V.0Gerget Olga M.1Massel Aleksei G.2Mamedov Timur G.3Melentiev Energy Systems Institute of SB RASTomsk Polytechnic University, Department of Information TechnologiesMelentiev Energy Systems Institute of SB RASMelentiev Energy Systems Institute of SB RASThe article discusses the application possibilities of machine learning methods (artificial neural networks (ANN) and genetic algorithms (GA) to form management actions when applying the concept of situational management for intelligent support of strategic decision-making on the development of energy. At the first stage, the application of ANN to classify extreme situations in the energy sector, to select the most effective management actions (preventive measures) in order to prevent a critical situation from developing into an emergency. Genetic algorithms are proposed to be used to determine the weighting coefficients for training ANN. An algorithm for constructing a classifier based on a neural network and a demonstration task using data on generation and consumption of the United Electric Power System of Siberia are presented.https://www.epj-conferences.org/articles/epjconf/pdf/2019/22/epjconf_freps18_01010.pdfsituational managementmachine learningartificial neural networksgenetic algorithmsextreme situations in the energy sectormanagement actions (preventive measures). |
| spellingShingle | Massel Lyudmila V. Gerget Olga M. Massel Aleksei G. Mamedov Timur G. The Use of Machine Learning in Situational Management in Relation to the Tasks of the Power Industry EPJ Web of Conferences situational management machine learning artificial neural networks genetic algorithms extreme situations in the energy sector management actions (preventive measures). |
| title | The Use of Machine Learning in Situational Management in Relation to the Tasks of the Power Industry |
| title_full | The Use of Machine Learning in Situational Management in Relation to the Tasks of the Power Industry |
| title_fullStr | The Use of Machine Learning in Situational Management in Relation to the Tasks of the Power Industry |
| title_full_unstemmed | The Use of Machine Learning in Situational Management in Relation to the Tasks of the Power Industry |
| title_short | The Use of Machine Learning in Situational Management in Relation to the Tasks of the Power Industry |
| title_sort | use of machine learning in situational management in relation to the tasks of the power industry |
| topic | situational management machine learning artificial neural networks genetic algorithms extreme situations in the energy sector management actions (preventive measures). |
| url | https://www.epj-conferences.org/articles/epjconf/pdf/2019/22/epjconf_freps18_01010.pdf |
| work_keys_str_mv | AT massellyudmilav theuseofmachinelearninginsituationalmanagementinrelationtothetasksofthepowerindustry AT gergetolgam theuseofmachinelearninginsituationalmanagementinrelationtothetasksofthepowerindustry AT masselalekseig theuseofmachinelearninginsituationalmanagementinrelationtothetasksofthepowerindustry AT mamedovtimurg theuseofmachinelearninginsituationalmanagementinrelationtothetasksofthepowerindustry AT massellyudmilav useofmachinelearninginsituationalmanagementinrelationtothetasksofthepowerindustry AT gergetolgam useofmachinelearninginsituationalmanagementinrelationtothetasksofthepowerindustry AT masselalekseig useofmachinelearninginsituationalmanagementinrelationtothetasksofthepowerindustry AT mamedovtimurg useofmachinelearninginsituationalmanagementinrelationtothetasksofthepowerindustry |