{"title":"动态混沌条件下统计预测方法效率评价","authors":"R. Yusupov, A. A. Musaev, D. A. Grigoriev","doi":"10.1109/CTS53513.2021.9562780","DOIUrl":null,"url":null,"abstract":"The current article dedicated to analyzing the feasibility of using conventional techniques of statistical synthesis of prognostic decisions in the conditions of dynamic chaos, which characterizes management in unstable submersion environments. We show the fundamental difference between unstable system state observation series and probabilistic descriptions of traditional models based on the statistical paradigm. We consider an additive model with a chaotic systemic component and non-stationary noise, which describes the aforementioned observation series most adequately. We propose a method for pragmatic estimation of functional efficiency of forecast techniques in the conditions of chaotic non-determinism.","PeriodicalId":371882,"journal":{"name":"2021 IV International Conference on Control in Technical Systems (CTS)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Evaluation of Statistical Forecast Method Efficiency in the Conditions of Dynamic Chaos\",\"authors\":\"R. Yusupov, A. A. Musaev, D. A. Grigoriev\",\"doi\":\"10.1109/CTS53513.2021.9562780\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The current article dedicated to analyzing the feasibility of using conventional techniques of statistical synthesis of prognostic decisions in the conditions of dynamic chaos, which characterizes management in unstable submersion environments. We show the fundamental difference between unstable system state observation series and probabilistic descriptions of traditional models based on the statistical paradigm. We consider an additive model with a chaotic systemic component and non-stationary noise, which describes the aforementioned observation series most adequately. We propose a method for pragmatic estimation of functional efficiency of forecast techniques in the conditions of chaotic non-determinism.\",\"PeriodicalId\":371882,\"journal\":{\"name\":\"2021 IV International Conference on Control in Technical Systems (CTS)\",\"volume\":\"12 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-09-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IV International Conference on Control in Technical Systems (CTS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CTS53513.2021.9562780\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IV International Conference on Control in Technical Systems (CTS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CTS53513.2021.9562780","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Evaluation of Statistical Forecast Method Efficiency in the Conditions of Dynamic Chaos
The current article dedicated to analyzing the feasibility of using conventional techniques of statistical synthesis of prognostic decisions in the conditions of dynamic chaos, which characterizes management in unstable submersion environments. We show the fundamental difference between unstable system state observation series and probabilistic descriptions of traditional models based on the statistical paradigm. We consider an additive model with a chaotic systemic component and non-stationary noise, which describes the aforementioned observation series most adequately. We propose a method for pragmatic estimation of functional efficiency of forecast techniques in the conditions of chaotic non-determinism.