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Titlebook: Beyond Traditional Probabilistic Data Processing Techniques: Interval, Fuzzy etc. Methods and Their ; Olga Kosheleva,Sergey P. Shary,Roman

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發(fā)表于 2025-3-21 16:06:22 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱Beyond Traditional Probabilistic Data Processing Techniques: Interval, Fuzzy etc. Methods and Their
影響因子2023Olga Kosheleva,Sergey P. Shary,Roman Zapatrin
視頻videohttp://file.papertrans.cn/186/185293/185293.mp4
發(fā)行地址This book is about going beyond traditional probabilistic data processing techniques, to pursue interval, fuzzy, etc. methods – how to do it, and what the applications of the resulting non-traditional
學(xué)科分類Studies in Computational Intelligence
圖書封面Titlebook: Beyond Traditional Probabilistic Data Processing Techniques: Interval, Fuzzy etc. Methods and Their ; Olga Kosheleva,Sergey P. Shary,Roman
影響因子Data processing has become essential to modern civilization. The original data for this processing comes from measurements or from experts, and both sources are subject to uncertainty. Traditionally, probabilistic methods have been used to process uncertainty. However, in many practical situations, we do not know the corresponding probabilities: in measurements, we often only know the upper bound on the measurement errors; this is known as interval uncertainty. In turn, expert estimates often include imprecise (fuzzy) words from natural language such as "small"; this is known as fuzzy uncertainty.?.In this book, leading specialists on interval, fuzzy, probabilistic uncertainty and their combination describe state-of-the-art developments in their research areas. Accordingly, the book offers a valuable guide for researchers and practitioners interested in data processing under uncertainty, and an introduction to the latest trends and techniques in this area, suitablefor graduate students.?.
Pindex Book 2020
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發(fā)表于 2025-3-21 20:28:35 | 只看該作者
Strengths of Fuzzy Techniques in Data Scienceh statistical approaches are often presented as major tools to cope with big data and modern user expectations of their exploitation. The multiple capacities of fuzzy and related knowledge representation methods make them inescapable to deal with various types of uncertainty inherent in all kinds of data.
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發(fā)表于 2025-3-22 09:03:06 | 只看該作者
Trade, Skill Formation and the Wage-GapThe basic definitions of the concept of interval-valued intuitionistic fuzzy set and of the operations, relations and operators over it are given. Some of ita most important applications are described. Ideas for future development of the theory of interval-valued intuitionistic fuzzy sets are discussed.
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發(fā)表于 2025-3-22 15:07:19 | 只看該作者
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發(fā)表于 2025-3-22 20:48:13 | 只看該作者
https://doi.org/10.1007/978-3-642-57422-1Picture fuzzy sets, recently introduced by B. C. Cuong and V. Kreinovich, are a special case of .-fuzzy sets. We discuss the set of truth values for these fuzzy sets as well as aggregation functions for these truth values, paying special attention to t-norms and t-conorms. The important role of representable t-norms and t-conorms is emphasized.
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發(fā)表于 2025-3-22 21:23:26 | 只看該作者
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發(fā)表于 2025-3-23 05:14:04 | 只看該作者
Interval Valued Intuitionistic Fuzzy Sets Past, Present and FutureThe basic definitions of the concept of interval-valued intuitionistic fuzzy set and of the operations, relations and operators over it are given. Some of ita most important applications are described. Ideas for future development of the theory of interval-valued intuitionistic fuzzy sets are discussed.
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發(fā)表于 2025-3-23 09:20:27 | 只看該作者
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