{"title":"REAL-TIME MANAGEMENT OF CRITICAL IT-SYSTEMS \nBASED ON NEURAL NETWORK TECHNOLOGIES","authors":"A. Starovoytov, V. Krasnoproshin","doi":"10.52928/2070-1624-2024-42-1-18-25","DOIUrl":null,"url":null,"abstract":"The paper investigates a relevant applied problem associated with building decision support systems for critical \ninformation services. An original approach is proposed, based on neural network forecasting, within which \na method of dynamic local approximation using neural network models has been developed. The principles of constructing \nand implementing the operational algorithm (under conditions of uncertainty of the external load profile) \nof a combined proactive system for managing computational resources are outlined. Experiments have been conducted \nthat confirm the effectiveness of the method and the approach as a whole.","PeriodicalId":386243,"journal":{"name":"HERALD OF POLOTSK STATE UNIVERSITY. Series С FUNDAMENTAL SCIENCES","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"HERALD OF POLOTSK STATE UNIVERSITY. Series С FUNDAMENTAL SCIENCES","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.52928/2070-1624-2024-42-1-18-25","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
The paper investigates a relevant applied problem associated with building decision support systems for critical
information services. An original approach is proposed, based on neural network forecasting, within which
a method of dynamic local approximation using neural network models has been developed. The principles of constructing
and implementing the operational algorithm (under conditions of uncertainty of the external load profile)
of a combined proactive system for managing computational resources are outlined. Experiments have been conducted
that confirm the effectiveness of the method and the approach as a whole.