Uncertainty Data in Interval-Valued Fuzzy Set Theory

Uncertainty Data in Interval-Valued Fuzzy Set Theory PDF Author: Barbara Pękala
Publisher: Springer
ISBN: 3319939106
Category : Technology & Engineering
Languages : en
Pages : 181

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Book Description
This book offers an introduction to fuzzy sets theory and their operations, with a special focus on aggregation and negation functions. Particular attention is given to interval-valued fuzzy sets and Atanassov’s intuitionistic fuzzy sets and their use in uncertainty models involving imperfect or unknown information. The theory and application of interval-values fuzzy sets to various decision making problems represent the central core of this book, which describes in detail aggregation operators and their use with imprecise data represented as intervals. Interval-valued fuzzy relations, compatibility measures of interval and the transitivity property are thoroughly covered. With its good balance between theoretical considerations and applications of originally developed algorithms to real-world problem, the book offers a timely, inspiring guide to mathematicians and engineers developing new decision making models or implementing/applying existing ones to a wide range of applications involving imprecise or incomplete data.

Uncertainty Data in Interval-valued Fuzzy Set Theory

Uncertainty Data in Interval-valued Fuzzy Set Theory PDF Author: Barbara Pe̜kala
Publisher:
ISBN: 9783319939117
Category : Fuzzy sets
Languages : en
Pages : 181

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Book Description
This book offers an introduction to fuzzy sets theory and their operations, with a special focus on aggregation and negation functions. Particular attention is given to interval-valued fuzzy sets and Atanassov's intuitionistic fuzzy sets and their use in uncertainty models involving imperfect or unknown information. The theory and application of interval-values fuzzy sets to various decision making problems represent the central core of this book, which describes in detail aggregation operators and their use with imprecise data represented as intervals. Interval-valued fuzzy relations, compatibility measures of interval and the transitivity property are thoroughly covered. With its good balance between theoretical considerations and applications of originally developed algorithms to real-world problem, the book offers a timely, inspiring guide to mathematicians and engineers developing new decision making models or implementing/applying existing ones to a wide range of applications involving imprecise or incomplete data.

Information Processing and Management of Uncertainty in Knowledge-Based Systems

Information Processing and Management of Uncertainty in Knowledge-Based Systems PDF Author: Davide Ciucci
Publisher: Springer Nature
ISBN: 3031089715
Category : Computers
Languages : en
Pages : 825

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Book Description
This two-volume set (CCIS 1601-1602) constitutes the proceedings of the 19th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2021, held in Milan, Italy, in July 2022. The 124 papers were carefully reviewed and selected from 188 submissions. The papers are organized in topical sections as follows: aggregation theory beyond the unit interval; formal concept analysis and uncertainty; fuzzy implication functions; fuzzy mathematical analysis and its applications; generalized sets and operators; information fusion techniques based on aggregation functions, pre-aggregation functions, and their generalizations; interval uncertainty; knowledge acquisition, representation and reasoning; logical structures of opposition and logical syllogisms; mathematical fuzzy logics; theoretical and applied aspects of imprecise probabilities; data science and machine learning; decision making modeling and applications; e-health; fuzzy methods in data mining and knowledge discovery; soft computing and artificia intelligence techniques in image processing; soft methods in statistics and data analysis; uncertainty, heterogeneity, reliability and explainability in AI; weak and cautious supervised learning.

Logarithmic Similarity Measure between Interval-Valued Fuzzy Sets and Its Fault Diagnosis Method

Logarithmic Similarity Measure between Interval-Valued Fuzzy Sets and Its Fault Diagnosis Method PDF Author: Zhikang Lu
Publisher: Infinite Study
ISBN:
Category :
Languages : en
Pages : 12

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Book Description
Fault diagnosis is an important task for the normal operation and maintenance of equipment. In many real situations, the diagnosis data cannot provide deterministic values and are usually imprecise or uncertain. Thus, interval-valued fuzzy sets (IVFSs) are very suitable for expressing imprecise or uncertain fault information in real problems.

Uncertainty and Imprecision in Decision Making and Decision Support - New Advances, Challenges, and Perspectives

Uncertainty and Imprecision in Decision Making and Decision Support - New Advances, Challenges, and Perspectives PDF Author: Krassimir T. Atanassov
Publisher: Springer Nature
ISBN: 3031450698
Category : Technology & Engineering
Languages : en
Pages : 353

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Book Description
This volume is composed of selected papers from two conferences held in Warsaw, Poland on October 13-15, 2022: the BOS/SOR’2022 - National Conference on Operational and Systems Research, one of premiere conferences in the field of operational and systems research, and the Twentith International Workshop on Intuitionistic Fuzzy Sets and Generalized Nets, IWIFSGN-2022, 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). 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 their related tools and techniques.

Interval-Valued Methods in Classifications and Decisions

Interval-Valued Methods in Classifications and Decisions PDF Author: Urszula Bentkowska
Publisher: Springer
ISBN: 3030129276
Category : Technology & Engineering
Languages : en
Pages : 163

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Book Description
This book describes novel algorithms based on interval-valued fuzzy methods that are expected to improve classification and decision-making processes under incomplete or imprecise information. At first, it introduces interval-valued fuzzy sets. It then discusses new methods for aggregation on interval-valued settings, and the most common properties of interval-valued aggregation operators. It then presents applications such as decision making using interval-valued aggregation, and classification in case of missing values. Interesting applications of the developed algorithms to DNA microarray analysis and in medical decision support systems are shown. The book is intended not only as a timely report for the community working on fuzzy sets and their extensions but also for researchers and practitioners dealing with the problems of uncertain or imperfect information.

Intelligent Systems'2014

Intelligent Systems'2014 PDF Author: P. Angelov
Publisher: Springer
ISBN: 3319113135
Category : Technology & Engineering
Languages : en
Pages : 864

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Book Description
This two volume set of books constitutes the proceedings of the 2014 7th IEEE International Conference Intelligent Systems (IS), or IEEE IS’2014 for short, held on September 24–26, 2014 in Warsaw, Poland. Moreover, it contains some selected papers from the collocated IWIFSGN'2014 ‐ Thirteenth International Workshop on Intuitionistic Fuzzy Sets and Generalized Nets. The conference was organized by theSystems Research Institute, Polish Academy of Sciences, Department IV of Engineering Sciences, Polish Academy of Sciences, and Industrial Institute of Automation and Measurements – PIAP. The papers included in the two proceedings volumes have been subject to a thorough review process by three highly qualified peer reviewers.Comments and suggestions from them have considerable helped improve the quality of the papers but also the division of the volumes into parts, and assignment of the papers to the best suited parts.

Uncertainty Modelling in Data Science

Uncertainty Modelling in Data Science PDF Author: Sébastien Destercke
Publisher: Springer
ISBN: 3319975471
Category : Technology & Engineering
Languages : en
Pages : 234

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Book Description
This book features 29 peer-reviewed papers presented at the 9th International Conference on Soft Methods in Probability and Statistics (SMPS 2018), which was held in conjunction with the 5th International Conference on Belief Functions (BELIEF 2018) in Compiègne, France on September 17–21, 2018. It includes foundational, methodological and applied contributions on topics as varied as imprecise data handling, linguistic summaries, model coherence, imprecise Markov chains, and robust optimisation. These proceedings were produced using EasyChair. Over recent decades, interest in extensions and alternatives to probability and statistics has increased significantly in diverse areas, including decision-making, data mining and machine learning, and optimisation. This interest stems from the need to enrich existing models, in order to include different facets of uncertainty, like ignorance, vagueness, randomness, conflict or imprecision. Frameworks such as rough sets, fuzzy sets, fuzzy random variables, random sets, belief functions, possibility theory, imprecise probabilities, lower previsions, and desirable gambles all share this goal, but have emerged from different needs. The advances, results and tools presented in this book are important in the ubiquitous and fast-growing fields of data science, machine learning and artificial intelligence. Indeed, an important aspect of some of the learned predictive models is the trust placed in them. Modelling the uncertainty associated with the data and the models carefully and with principled methods is one of the means of increasing this trust, as the model will then be able to distinguish between reliable and less reliable predictions. In addition, extensions such as fuzzy sets can be explicitly designed to provide interpretable predictive models, facilitating user interaction and increasing trust.

Information Processing and Management of Uncertainty in Knowledge-Based Systems

Information Processing and Management of Uncertainty in Knowledge-Based Systems PDF Author: Marie-Jeanne Lesot
Publisher: Springer Nature
ISBN: 3030501434
Category : Computers
Languages : en
Pages : 816

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Book Description
This three volume set (CCIS 1237-1239) constitutes the proceedings of the 18th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2020, in June 2020. The conference was scheduled to take place in Lisbon, Portugal, at University of Lisbon, but due to COVID-19 pandemic it was held virtually. The 173 papers were carefully reviewed and selected from 213 submissions. The papers are organized in topical sections: homage to Enrique Ruspini; invited talks; foundations and mathematics; decision making, preferences and votes; optimization and uncertainty; games; real world applications; knowledge processing and creation; machine learning I; machine learning II; XAI; image processing; temporal data processing; text analysis and processing; fuzzy interval analysis; theoretical and applied aspects of imprecise probabilities; similarities in artificial intelligence; belief function theory and its applications; aggregation: theory and practice; aggregation: pre-aggregation functions and other generalizations of monotonicity; aggregation: aggregation of different data structures; fuzzy methods in data mining and knowledge discovery; computational intelligence for logistics and transportation problems; fuzzy implication functions; soft methods in statistics and data analysis; image understanding and explainable AI; fuzzy and generalized quantifier theory; mathematical methods towards dealing with uncertainty in applied sciences; statistical image processing and analysis, with applications in neuroimaging; interval uncertainty; discrete models and computational intelligence; current techniques to model, process and describe time series; mathematical fuzzy logic and graded reasoning models; formal concept analysis, rough sets, general operators and related topics; computational intelligence methods in information modelling, representation and processing.

Proceedings of International Conference on Image, Vision and Intelligent Systems 2022 (ICIVIS 2022)

Proceedings of International Conference on Image, Vision and Intelligent Systems 2022 (ICIVIS 2022) PDF Author: Peng You
Publisher: Springer Nature
ISBN: 9819909236
Category : Technology & Engineering
Languages : en
Pages : 1066

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Book Description
This book is a collection of the papers accepted by the ICIVIS 2022—The International Conference on Image, Vision and Intelligent Systems, held on August 15–17, 2022, in Jinan, China. The topics focus but are not limited to image, vision and intelligent systems. Each part can be used as an excellent reference by industry practitioners, university faculties, research fellows and undergraduates as well as graduate students who need to build a knowledge base of the most current advances and state of practice in the topics covered by this conference proceedings.