Intelligent risk management systems in european energy markets

O.A. Poplavskyi, O.I. Soroka, M.O. Litvin, A.V. Poplavskyi
{"title":"Intelligent risk management systems in european energy markets","authors":"O.A. Poplavskyi, O.I. Soroka, M.O. Litvin, A.V. Poplavskyi","doi":"10.31649/1681-7893-2024-47-1-233-239","DOIUrl":null,"url":null,"abstract":"Based on machine learning algorithms, a method for predicting risks in the European energy markets has been proposed. The work is aimed at developing intelligent risk management systems that utilize advanced artificial intelligence technologies for assessing and minimizing potential threats. Utilizing historical data and current market trends, a comprehensive approach to identifying price volatility and risk zones in the energy markets is presented. The study demonstrates how artificial intelligence can enhance the effectiveness of decisions made by managers in the energy markets and ensure more sustainable resource management in conditions of increasing uncertainty. The results show that the use of complex machine learning algorithms and data analysis can significantly improve the accuracy of risk prediction and contribute to the adoption of well-founded managerial decisions.","PeriodicalId":509753,"journal":{"name":"Optoelectronic Information-Power Technologies","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Optoelectronic Information-Power Technologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.31649/1681-7893-2024-47-1-233-239","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Based on machine learning algorithms, a method for predicting risks in the European energy markets has been proposed. The work is aimed at developing intelligent risk management systems that utilize advanced artificial intelligence technologies for assessing and minimizing potential threats. Utilizing historical data and current market trends, a comprehensive approach to identifying price volatility and risk zones in the energy markets is presented. The study demonstrates how artificial intelligence can enhance the effectiveness of decisions made by managers in the energy markets and ensure more sustainable resource management in conditions of increasing uncertainty. The results show that the use of complex machine learning algorithms and data analysis can significantly improve the accuracy of risk prediction and contribute to the adoption of well-founded managerial decisions.
欧洲能源市场的智能风险管理系统
基于机器学习算法,提出了一种预测欧洲能源市场风险的方法。这项工作旨在开发智能风险管理系统,利用先进的人工智能技术来评估和尽量减少潜在威胁。利用历史数据和当前市场趋势,提出了一种识别能源市场价格波动和风险区域的综合方法。该研究展示了人工智能如何提高能源市场管理人员决策的有效性,并确保在不确定性不断增加的情况下实现更可持续的资源管理。研究结果表明,使用复杂的机器学习算法和数据分析可以显著提高风险预测的准确性,有助于采用有充分依据的管理决策。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信