模糊方法在实际应用中的新前景

IF 1.5 Q2 COMPUTER SCIENCE, THEORY & METHODS International Journal of Fuzzy Logic and Intelligent Systems Pub Date : 2021-04-13 DOI:10.3233/JIFS-189896
E. Isaeva, Á. Rocha
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引用次数: 0

摘要

在当今数字化无处不在的时代,人类生活几乎所有领域对自动化的需求都变得前所未有的高。常规过程的自动化使得实现更高的性能、更低的成本和人工实现的工作量,以及更可行的资源和劳动力的重新分配成为可能。为了在人类生活的许多方面实现自动化,有必要处理真实的信息。就自动化信息处理而言,“信息是对分析师对不确定性的评估有影响的一切。”这种不确定性可以有不同的类型:数据不确定性、非确定性数量、模型不确定性和先验信息的不确定性。测量结果和观测数据是特殊形式的信息。这样的数据通常不是精确的数字,而是或多或少不精确的,也被称为模糊的“[3]”。处理这种不精确和嘈杂的数据需要建立一种灵活和自适应的方法来处理信息,并开发方法来提高管理涉及非概率不确定性的复杂优化和决策方面的能力,从而理解、开发和实践在经济、工程、管理和社会问题等领域使用的模糊技术。模糊概念在数学、信息技术和工程领域中出现的时间很长
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New vistas of fuzzy methods in real life application
In the current era of pervasive digitalization, the 7 demand for automation of nearly all spheres of human 8 life has become unprecedentedly high. Automation of 9 routine processes make it possible to achieve higher 10 performance, lower costs and effort on their manual 11 implementation, along with a more viable realloca12 tion of resources and labor contribution. To achieve 13 automation in many aspects of human life, it is nec14 essary to deal with real information. In terms of 15 automated information processing, “information is 16 everything which has influence on the assessment of 17 uncertainty by an analyst. This uncertainty can be 18 of different types: data uncertainty, nondeterminis19 tic quantities, model uncertainty, and uncertainty of 20 a priori information. Measurement results and obser21 vational data are special forms of information. Such 22 data are frequently not precise numbers but more or 23 less non-precise, also called fuzzy” [3]. Operating 24 such kind of imprecise and noisy data requires the 25 establishment of a flexible and adaptive approach 26 to information processing and the development of 27 methodologies to enhance the ability to manage com28 plicated optimization and decision making aspects 29 involving non-probabilistic uncertainty with the rea30 son to understand, develop, and practice the fuzzy 31 technologies to be used in fields such as economic, 32 engineering, management, and societal problems [1]. 33 The idea of fuzziness in the field of mathemat34 ics, Information technologies, and engineering dates 35
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来源期刊
CiteScore
2.80
自引率
23.10%
发文量
31
期刊介绍: The International Journal of Fuzzy Logic and Intelligent Systems (pISSN 1598-2645, eISSN 2093-744X) is published quarterly by the Korean Institute of Intelligent Systems. The official title of the journal is International Journal of Fuzzy Logic and Intelligent Systems and the abbreviated title is Int. J. Fuzzy Log. Intell. Syst. Some, or all, of the articles in the journal are indexed in SCOPUS, Korea Citation Index (KCI), DOI/CrossrRef, DBLP, and Google Scholar. The journal was launched in 2001 and dedicated to the dissemination of well-defined theoretical and empirical studies results that have a potential impact on the realization of intelligent systems based on fuzzy logic and intelligent systems theory. Specific topics include, but are not limited to: a) computational intelligence techniques including fuzzy logic systems, neural networks and evolutionary computation; b) intelligent control, instrumentation and robotics; c) adaptive signal and multimedia processing; d) intelligent information processing including pattern recognition and information processing; e) machine learning and smart systems including data mining and intelligent service practices; f) fuzzy theory and its applications.
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