{"title":"用于预测和控制支持的三维系统-物体分类","authors":"S. I. Matorin, S. V. Gul, N. V. Shcherbinina","doi":"10.3103/S0005105523060067","DOIUrl":null,"url":null,"abstract":"<p>The disadvantages of modern methods of classifying objects and processes are considered. We propose a method of constructing three-dimensional classifications that allows the elimination of some of these shortcomings, based on the system-object approach, using the ideas of multidimensional classification and natural classification. Three basic system characteristics are used as classification planes: structural (node), functional (function), and substantive (object), which allows for the classification by types of functional request to the system from a higher-order system (supersystem) by types of system formation processes and by the obtained results. Each classification is a tree-type graph with one vertex that is common to all three planes. The formal description of the three-dimensional graph by means of descriptive logic is presented, which not only allows for the phenomena and objects of the subject area to be classified, but also for the cause-and-effect relations existing in this area to be traced. The procedures for the use of three-dimensional system-object classification for forecasting and management support are described. An example of three-dimensional classification for functional diagnostic devices is given.</p>","PeriodicalId":42995,"journal":{"name":"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS","volume":null,"pages":null},"PeriodicalIF":0.5000,"publicationDate":"2024-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Three-Dimensional System-Object Classification for Prediction and Control Support\",\"authors\":\"S. I. Matorin, S. V. Gul, N. V. Shcherbinina\",\"doi\":\"10.3103/S0005105523060067\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>The disadvantages of modern methods of classifying objects and processes are considered. We propose a method of constructing three-dimensional classifications that allows the elimination of some of these shortcomings, based on the system-object approach, using the ideas of multidimensional classification and natural classification. Three basic system characteristics are used as classification planes: structural (node), functional (function), and substantive (object), which allows for the classification by types of functional request to the system from a higher-order system (supersystem) by types of system formation processes and by the obtained results. Each classification is a tree-type graph with one vertex that is common to all three planes. The formal description of the three-dimensional graph by means of descriptive logic is presented, which not only allows for the phenomena and objects of the subject area to be classified, but also for the cause-and-effect relations existing in this area to be traced. The procedures for the use of three-dimensional system-object classification for forecasting and management support are described. An example of three-dimensional classification for functional diagnostic devices is given.</p>\",\"PeriodicalId\":42995,\"journal\":{\"name\":\"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.5000,\"publicationDate\":\"2024-02-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://link.springer.com/article/10.3103/S0005105523060067\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.3103/S0005105523060067","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
Three-Dimensional System-Object Classification for Prediction and Control Support
The disadvantages of modern methods of classifying objects and processes are considered. We propose a method of constructing three-dimensional classifications that allows the elimination of some of these shortcomings, based on the system-object approach, using the ideas of multidimensional classification and natural classification. Three basic system characteristics are used as classification planes: structural (node), functional (function), and substantive (object), which allows for the classification by types of functional request to the system from a higher-order system (supersystem) by types of system formation processes and by the obtained results. Each classification is a tree-type graph with one vertex that is common to all three planes. The formal description of the three-dimensional graph by means of descriptive logic is presented, which not only allows for the phenomena and objects of the subject area to be classified, but also for the cause-and-effect relations existing in this area to be traced. The procedures for the use of three-dimensional system-object classification for forecasting and management support are described. An example of three-dimensional classification for functional diagnostic devices is given.
期刊介绍:
Automatic Documentation and Mathematical Linguistics is an international peer reviewed journal that covers all aspects of automation of information processes and systems, as well as algorithms and methods for automatic language analysis. Emphasis is on the practical applications of new technologies and techniques for information analysis and processing.