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Titlebook: Uncertainty and Imprecision in Decision Making and Decision Support: New Advances, Challenges, and P; Selected papers from Krassimir T. Ata

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發(fā)表于 2025-3-21 16:33:36 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Uncertainty and Imprecision in Decision Making and Decision Support: New Advances, Challenges, and P
副標題Selected papers from
編輯Krassimir T. Atanassov,Vassia Atanassova,S?awomir
視頻videohttp://file.papertrans.cn/942/941123/941123.mp4
概述Presents recent research in fuzzy logic and technology.Is composed of selected papers presented at IWIFSGN 2020 and BOS-2020.Provides recent research in uncertainty and imprecision in decision making
叢書名稱Lecture Notes in Networks and Systems
圖書封面Titlebook: Uncertainty and Imprecision in Decision Making and Decision Support: New Advances, Challenges, and P; Selected papers from Krassimir T. Ata
描述.This book is composed of selected papers from the Sixteenth National Conference on Operational and Systems Research, BOS-2020, held on December 14-15, 2020, one of premiere conferences in the field of operational and systems research. The second is the Nineteenth International Workshop on Intuitionistic Fuzzy Sets and Generalized Nets, IWIFSGN 2020, held on December 10-11, 2020, in Warsaw, Poland, in turn—one of premiere conferences on fuzzy logic, notably on extensions of the traditional fuzzy sets, also comprising a considerable part on the generalized nets (GNs), an important extension of the traditional Petri nets. A joint publication of selected papers from the two conferences follows a long tradition of such a joint organization and—from a substantial point of view—combines systems modeling, systems analysis, broadly perceived operational research, notably optimization, decision making, and decision support, with various aspects of uncertain and imprecise information and theirrelated tools and techniques. .
出版日期Conference proceedings 2022
關(guān)鍵詞Intelligent Systems; Fuzzy Logic; Intuitionistic Fuzzy Sets; Generalized Nets; IWIFSGN 2020; BOS 2020
版次1
doihttps://doi.org/10.1007/978-3-030-95929-6
isbn_softcover978-3-030-95928-9
isbn_ebook978-3-030-95929-6Series ISSN 2367-3370 Series E-ISSN 2367-3389
issn_series 2367-3370
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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發(fā)表于 2025-3-21 22:08:14 | 只看該作者
Uncertainty and Imprecision in Decision Making and Decision Support: New Advances, Challenges, and P978-3-030-95929-6Series ISSN 2367-3370 Series E-ISSN 2367-3389
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發(fā)表于 2025-3-22 08:13:26 | 只看該作者
Krassimir T. Atanassov,Vassia Atanassova,S?awomir Presents recent research in fuzzy logic and technology.Is composed of selected papers presented at IWIFSGN 2020 and BOS-2020.Provides recent research in uncertainty and imprecision in decision making
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發(fā)表于 2025-3-22 11:38:58 | 只看該作者
Lecture Notes in Networks and Systemshttp://image.papertrans.cn/u/image/941123.jpg
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Application of Decision Rules to Discover Knowledge for Fitting Aggregations to Datasetsbased on the dataset complexity measures. In discovering knowledge we apply the existing toolset RSES. We consider examples of feature-based measures, dimensionality measures, measures of separability of classes, and class imbalance measures to reflect the complexity of the classification problem.
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發(fā)表于 2025-3-22 23:39:28 | 只看該作者
Conditional Intuitionistic Fuzzy Mean Value in Connection with IF-Probability an intuitionistic fuzzy probability. We show the relation between a conditional intuitionistic fuzzy mean value and conditional intuitionistic fuzzy probability related to the intuitionistic fuzzy probability. We formulate the martingale convergence theorem for a conditional intuitionistic fuzzy mean value in this case, too.
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發(fā)表于 2025-3-23 05:14:43 | 只看該作者
An Interval-Valued Intuitionistic Fuzzy Estimation of?the?Area of?2D-Figures Based on?Pick’s Formulased on an iterative procedure for estimation of the area surrounded by a simple closed curve in the real 2D space. Pick’s Formula is employed for calculating the area surrounded by a special types of polygons. The result is a numerical method permitting the implementation of the algorithm in any procedural programming language.
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