Analysis and review on fuzzy evaluation of the performance

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dc.contributor.authorYu, Junfeng
dc.contributor.authorYang, Zijiang
dc.contributor.authorGuo, Jianping
dc.contributor.authorGloba, Larysa
dc.date.accessioned2022-04-27T14:52:38Z
dc.date.available2022-04-27T14:52:38Z
dc.date.issued2021
dc.description.abstractenIn modern conditions a comprehensive analysis of development trends and their effectiveness in various areas of human activity increasingly requires the analysis of data accumulated in numerous documents stored on the global network. Such an analysis is based on annual results in many areas of research, time trends and keywords. This analysis has certain peculiarities: it requires an analysis of not always accurate numerical information, comparison of qualitative indicators, obtaining both qualitative and quantitative characteristics, as well as the use of reference information for researchers and decision makers in related fields. In this regard, in recent years, a fuzzy assessment based on fuzzy mathematics is increasingly used in all types of assessing the effectiveness of various activities. The paper deals with conducting a bibliometric study based on the Extended Science Citation Index (SCI-E) and fuzzy performance measures to understand research trends and areas of focus. This paper takes the relevant scientific papers in Web of Science database as the research object, and analyzes the research trends with the help of bibliometrics. The results show that the number of papers published in the world is on the rise. The number of papers published in China and Iran is higher than that in other countries and regions. However, the number of papers cited in the United States and Turkey is higher than that in other countries or regions. Islamic Azad University is the largest. The research topics focus on fuzzy sets, fuzzy logic, genetic algorithms and performance evaluation. The research hotspots before 2011 included expert systems, neuro-fuzzy systems, and pattern recognition. After 2011, the research hotspots became neural networks, fuzzy sets, and machine learning.uk
dc.format.pagerangeС. 86-98uk
dc.identifier.citationAnalysis and review on fuzzy evaluation of the performance / Junfeng Yu, Zijiang Yang, Jianping Guo, Larysa Globa // Системні дослідження та інформаційні технології : міжнародний науково-технічний журнал. – 2021. – № 3. – С. 86-98. – Бібліогр.: 16 назв.uk
dc.identifier.doihttps://doi.org/10.20535/SRIT.2308-8893.2021.3.07
dc.identifier.urihttps://ela.kpi.ua/handle/123456789/47032
dc.language.isoenuk
dc.publisherКПІ ім. Ігоря Сікорськогоuk
dc.publisher.placeКиївuk
dc.sourceСистемні дослідження та інформаційні технології: міжнародний науково-технічний журнал, № 3uk
dc.subjectinformation and communication networkuk
dc.subjectdata processing systemuk
dc.subjectontologyuk
dc.subjectmodeluk
dc.subjectanalysisuk
dc.subjectscalinguk
dc.subjectclassuk
dc.subjectrelationsuk
dc.subject.udc519-7.51uk
dc.titleAnalysis and review on fuzzy evaluation of the performanceuk
dc.typeArticleuk

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Системні дослідження та інформаційні технології: міжнародний науково-технічний журнал, № 3