Control Systems: Intellectualization As a Response to Challenges of the Big Data Era

IF 0.5 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS

AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS Pub Date : 2023-06-13 DOI:10.3103/S0005105523020048

M. I. Zabezhailo

{"title":"Control Systems: Intellectualization As a Response to Challenges of the Big Data Era","authors":"M. I. Zabezhailo","doi":"10.3103/S0005105523020048","DOIUrl":null,"url":null,"abstract":"<div><div><h3>\n <b>Abstract</b>—</h3><p>This article analyzes the problem of processing massive amounts of data under strict time constraints in control systems. One strategy for solving this problem involves the use of artificial intelligence (AI) technologies. The range of mathematical models traditionally used in control systems has been supplemented by AI-based solutions that involve computer-oriented formalizations of strategies used by human experts to solve problems of this type: so-called interpolation/extrapolation (I/E) models. This article discusses certain significant features of I/E-type solutions, in particular, their ability to generate effective solutions in open big data environments (where the behavior of the control object is not characterized by a single NORMAL state), the problem of identifying stable (inheritable) solutions in the set of permissible solutions when updating empirical data on behaviors of the control object, and finally the problem of identifying empirical dependencies of a causal nature in the current data to compile informal interpretations of alternatives (recommendations) generated by the digital control system to be presented to decision makers (DMs).</p></div></div>","PeriodicalId":42995,"journal":{"name":"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS","volume":null,"pages":null},"PeriodicalIF":0.5000,"publicationDate":"2023-06-13","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/S0005105523020048","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}

引用次数: 0

Abstract—

This article analyzes the problem of processing massive amounts of data under strict time constraints in control systems. One strategy for solving this problem involves the use of artificial intelligence (AI) technologies. The range of mathematical models traditionally used in control systems has been supplemented by AI-based solutions that involve computer-oriented formalizations of strategies used by human experts to solve problems of this type: so-called interpolation/extrapolation (I/E) models. This article discusses certain significant features of I/E-type solutions, in particular, their ability to generate effective solutions in open big data environments (where the behavior of the control object is not characterized by a single NORMAL state), the problem of identifying stable (inheritable) solutions in the set of permissible solutions when updating empirical data on behaviors of the control object, and finally the problem of identifying empirical dependencies of a causal nature in the current data to compile informal interpretations of alternatives (recommendations) generated by the digital control system to be presented to decision makers (DMs).

查看原文本刊更多论文

控制系统:智能化应对大数据时代的挑战

摘要——本文分析了控制系统在严格时间约束下处理大量数据的问题。解决这个问题的一个策略是使用人工智能技术。传统上用于控制系统的一系列数学模型得到了基于人工智能的解决方案的补充，这些解决方案涉及人类专家用于解决这类问题的策略的面向计算机的形式化：所谓的内插/外插（I/E）模型。本文讨论了I/E型解决方案的某些重要特征，特别是它们在开放的大数据环境中生成有效解决方案的能力（其中控制对象的行为不以单个NORMAL状态为特征），当更新关于控制对象的行为的经验数据时，在允许解的集合中识别稳定（可继承）解的问题，最后是识别当前数据中因果性质的经验依赖性的问题，以汇编数字控制系统生成的备选方案（建议）的非正式解释，并提交给决策者（DM）。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS COMPUTER SCIENCE, INFORMATION SYSTEMS-

自引率

40.00%

发文量

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.