{"title":"复杂结构对象技术条件的神经模糊分类","authors":"S. Mantserov","doi":"10.17587/it.29.91-97","DOIUrl":null,"url":null,"abstract":"The application of neural-fuzzy technologies for solving the problem of classification of states of objects of complex structure is considered. A quantitative assessment of the technical condition of the facility is proposed on the basis of a complex indicator — the technical condition index (ITS). The methodology of classification of technical conditions of objects of complex structure is based on the adaptive neural mesh interference system (ANFIS) and the neural mesh classifier (NNA), which significantly accelerated and improved the accuracy of calculations for effective management of these objects.","PeriodicalId":37476,"journal":{"name":"Radioelektronika, Nanosistemy, Informacionnye Tehnologii","volume":"7 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Neuro-Fuzzy Classification of Technical Conditions of Objects of Complex Structure\",\"authors\":\"S. Mantserov\",\"doi\":\"10.17587/it.29.91-97\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The application of neural-fuzzy technologies for solving the problem of classification of states of objects of complex structure is considered. A quantitative assessment of the technical condition of the facility is proposed on the basis of a complex indicator — the technical condition index (ITS). The methodology of classification of technical conditions of objects of complex structure is based on the adaptive neural mesh interference system (ANFIS) and the neural mesh classifier (NNA), which significantly accelerated and improved the accuracy of calculations for effective management of these objects.\",\"PeriodicalId\":37476,\"journal\":{\"name\":\"Radioelektronika, Nanosistemy, Informacionnye Tehnologii\",\"volume\":\"7 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-02-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Radioelektronika, Nanosistemy, Informacionnye Tehnologii\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.17587/it.29.91-97\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Materials Science\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Radioelektronika, Nanosistemy, Informacionnye Tehnologii","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.17587/it.29.91-97","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Materials Science","Score":null,"Total":0}
Neuro-Fuzzy Classification of Technical Conditions of Objects of Complex Structure
The application of neural-fuzzy technologies for solving the problem of classification of states of objects of complex structure is considered. A quantitative assessment of the technical condition of the facility is proposed on the basis of a complex indicator — the technical condition index (ITS). The methodology of classification of technical conditions of objects of complex structure is based on the adaptive neural mesh interference system (ANFIS) and the neural mesh classifier (NNA), which significantly accelerated and improved the accuracy of calculations for effective management of these objects.
期刊介绍：
Journal “Radioelectronics. Nanosystems. Information Technologies” (abbr RENSIT) publishes original articles, reviews and brief reports, not previously published, on topical problems in radioelectronics (including biomedical) and fundamentals of information, nano- and biotechnologies and adjacent areas of physics and mathematics. The authors of the journal are academicians, corresponding members and foreign members of the Russian Academy of Natural Sciences (RANS) and their colleagues, as well as other russian and foreign authors on the proposal of the members of RANS, which can be obtained by the author before sending articles to the editor or after its arrival on the recommendation of a member of the editorial board or another member of the RANS, who gave the opinion on the article at the request of the editior. The editors will accept articles in both Russian and English languages. Articles are internally peer reviewed (double-blind peer review) by members of the Editorial Board. Some articles undergo external review, if necessary. Designed for researchers, graduate students, physics students of senior courses and teachers. It turns out 2 times a year (that includes 2 rooms)
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