{"title":"REAL-TIME MANAGEMENT OF CRITICAL IT-SYSTEMS \u0000BASED ON NEURAL NETWORK TECHNOLOGIES","authors":"A. Starovoytov, V. Krasnoproshin","doi":"10.52928/2070-1624-2024-42-1-18-25","DOIUrl":"https://doi.org/10.52928/2070-1624-2024-42-1-18-25","url":null,"abstract":"The paper investigates a relevant applied problem associated with building decision support systems for critical \u0000information services. An original approach is proposed, based on neural network forecasting, within which \u0000a method of dynamic local approximation using neural network models has been developed. The principles of constructing \u0000and implementing the operational algorithm (under conditions of uncertainty of the external load profile) \u0000of a combined proactive system for managing computational resources are outlined. Experiments have been conducted \u0000that 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":0.0,"publicationDate":"2024-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140665654","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}