Knowledge Processing with Interval and Soft Computing

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Publisher : Springer Science & Business Media
ISBN 13 : 1848003269
Total Pages : 233 pages
Book Rating : 4.62/5 ( download)

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Book Synopsis Knowledge Processing with Interval and Soft Computing by : Chenyi Hu

Download or read book Knowledge Processing with Interval and Soft Computing written by Chenyi Hu and published by Springer Science & Business Media. This book was released on 2009-04-03 with total page 233 pages. Available in PDF, EPUB and Kindle. Book excerpt: Interval computing combined with fuzzy logic has become an emerging tool in studying artificial intelligence and knowledge processing (AIKP) applications since it models uncertainties frequently raised in the field. This book provides introductions for both interval and fuzzy computing in a very accessible style. Application algorithms covered in this book include quantitative and qualitative data mining with interval valued datasets, decision making systems with interval valued parameters, interval valued Nash games and interval weighted graphs. Successful applications in studying finance and economics, etc are also included. This book can serve as a handbook or a text for readers interested in applying interval and soft computing for AIKP.

Information Processing and Management of Uncertainty in Knowledge-Based Systems

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Publisher : Springer Nature
ISBN 13 : 3030501531
Total Pages : 839 pages
Book Rating : 4.32/5 ( download)

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Book Synopsis Information Processing and Management of Uncertainty in Knowledge-Based Systems by : Marie-Jeanne Lesot

Download or read book Information Processing and Management of Uncertainty in Knowledge-Based Systems written by Marie-Jeanne Lesot and published by Springer Nature. This book was released on 2020-06-05 with total page 839 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Information Processing and Management of Uncertainty in Knowledge-Based Systems

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Publisher : Springer Nature
ISBN 13 : 3031089715
Total Pages : 825 pages
Book Rating : 4.18/5 ( download)

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Book Synopsis Information Processing and Management of Uncertainty in Knowledge-Based Systems by : Davide Ciucci

Download or read book Information Processing and Management of Uncertainty in Knowledge-Based Systems written by Davide Ciucci and published by Springer Nature. This book was released on 2022-07-04 with total page 825 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Granular, Fuzzy, and Soft Computing

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Publisher : Springer Nature
ISBN 13 : 1071626280
Total Pages : 936 pages
Book Rating : 4.83/5 ( download)

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Book Synopsis Granular, Fuzzy, and Soft Computing by : Tsau-Young Lin

Download or read book Granular, Fuzzy, and Soft Computing written by Tsau-Young Lin and published by Springer Nature. This book was released on 2023-03-29 with total page 936 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first edition of the Encyclopedia of Complexity and Systems Science (ECSS, 2009) presented a comprehensive overview of granular computing (GrC) broadly divided into several categories: Granular computing from rough set theory, Granular Computing in Database Theory, Granular Computing in Social Networks, Granular Computing and Fuzzy Set Theory, Grid/Cloud Computing, as well as general issues in granular computing. In 2011, the formal theory of GrC was established, providing an adequate infrastructure to support revolutionary new approaches to computer/data science, including the challenges presented by so-called big data. For this volume of ECSS, Second Edition, many entries have been updated to capture these new developments, together with new chapters on such topics as data clustering, outliers in data mining, qualitative fuzzy sets, and information flow analysis for security applications. Granulations can be seen as a natural and ancient methodology deeply rooted in the human mind. Many daily "things" are routinely granulated into sub "things": The topography of earth is granulated into hills, plateaus, etc., space and time are granulated into infinitesimal granules, and a circle is granulated into polygons of infinitesimal sides. Such granules led to the invention of calculus, topology and non-standard analysis. Formalization of general granulation was difficult but, as shown in this volume, great progress has been made in combing discrete and continuous mathematics under one roof for a broad range of applications in data science.

Black Box Optimization, Machine Learning, and No-Free Lunch Theorems

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Publisher : Springer Nature
ISBN 13 : 3030665151
Total Pages : 388 pages
Book Rating : 4.59/5 ( download)

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Book Synopsis Black Box Optimization, Machine Learning, and No-Free Lunch Theorems by : Panos M. Pardalos

Download or read book Black Box Optimization, Machine Learning, and No-Free Lunch Theorems written by Panos M. Pardalos and published by Springer Nature. This book was released on 2021-05-27 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edited volume illustrates the connections between machine learning techniques, black box optimization, and no-free lunch theorems. Each of the thirteen contributions focuses on the commonality and interdisciplinary concepts as well as the fundamentals needed to fully comprehend the impact of individual applications and problems. Current theoretical, algorithmic, and practical methods used are provided to stimulate a new effort towards innovative and efficient solutions. The book is intended for beginners who wish to achieve a broad overview of optimization methods and also for more experienced researchers as well as researchers in mathematics, optimization, operations research, quantitative logistics, data analysis, and statistics, who will benefit from access to a quick reference to key topics and methods. The coverage ranges from mathematically rigorous methods to heuristic and evolutionary approaches in an attempt to equip the reader with different viewpoints of the same problem.

Concepts of Soft Computing

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Publisher : Springer
ISBN 13 : 9811374309
Total Pages : 195 pages
Book Rating : 4.02/5 ( download)

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Book Synopsis Concepts of Soft Computing by : Snehashish Chakraverty

Download or read book Concepts of Soft Computing written by Snehashish Chakraverty and published by Springer. This book was released on 2019-04-30 with total page 195 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses soft computing, which provides an efficient platform to deal with imprecision, uncertainty, vagueness and approximation in order to attain robustness and reliable computing. It explores two major concepts of soft computing: fuzzy set theory and neural networks, which relate to uncertainty handling and machine learning techniques respectively. Generally, fuzzy sets are considered as vague or uncertain sets having membership function lying between 0 and 1, and ANN is a type of artificial intelligence that attempts to imitate the way a human brain works by configuring specific applications, for instance pattern recognition or data classification, through learning processes. The book also presents C/MATLAB programming codes related to the basics of fuzzy set, interval arithmetic and ANN in a concise, practical and adaptable manner along, with simple examples and self-validation unsolved practice questions in few cases

Fuzzy Information Processing

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Publisher : Springer
ISBN 13 : 3319953125
Total Pages : 616 pages
Book Rating : 4.20/5 ( download)

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Book Synopsis Fuzzy Information Processing by : Guilherme A. Barreto

Download or read book Fuzzy Information Processing written by Guilherme A. Barreto and published by Springer. This book was released on 2018-07-03 with total page 616 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed proceedings of the 37th IFSA Conference, NAFIPS 2018, held in Fortaleza, Brazil, in July 2018. The 55 full papers presented were carefully reviewed and selected from 73 submissions. The papers deal with a large spectrum of topics, including theory and applications of fuzzy numbers and sets, fuzzy logic, fuzzy inference systems, fuzzy clustering, fuzzy pattern classification, neuro-fuzzy systems, fuzzy control systems, fuzzy modeling, fuzzy mathematical morphology, fuzzy dynamical systems, time series forecasting, and making decision under uncertainty.

Proceedings of the 12th International Conference on Soft Computing for Problem Solving

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Publisher : Springer Nature
ISBN 13 : 9819732921
Total Pages : 922 pages
Book Rating : 4.20/5 ( download)

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Book Synopsis Proceedings of the 12th International Conference on Soft Computing for Problem Solving by : Millie Pant

Download or read book Proceedings of the 12th International Conference on Soft Computing for Problem Solving written by Millie Pant and published by Springer Nature. This book was released on with total page 922 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Computing Statistics under Interval and Fuzzy Uncertainty

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Publisher : Springer
ISBN 13 : 3642249051
Total Pages : 412 pages
Book Rating : 4.51/5 ( download)

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Book Synopsis Computing Statistics under Interval and Fuzzy Uncertainty by : Hung T. Nguyen

Download or read book Computing Statistics under Interval and Fuzzy Uncertainty written by Hung T. Nguyen and published by Springer. This book was released on 2011-11-17 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: In many practical situations, we are interested in statistics characterizing a population of objects: e.g. in the mean height of people from a certain area. Most algorithms for estimating such statistics assume that the sample values are exact. In practice, sample values come from measurements, and measurements are never absolutely accurate. Sometimes, we know the exact probability distribution of the measurement inaccuracy, but often, we only know the upper bound on this inaccuracy. In this case, we have interval uncertainty: e.g. if the measured value is 1.0, and inaccuracy is bounded by 0.1, then the actual (unknown) value of the quantity can be anywhere between 1.0 - 0.1 = 0.9 and 1.0 + 0.1 = 1.1. In other cases, the values are expert estimates, and we only have fuzzy information about the estimation inaccuracy. This book shows how to compute statistics under such interval and fuzzy uncertainty. The resulting methods are applied to computer science (optimal scheduling of different processors), to information technology (maintaining privacy), to computer engineering (design of computer chips), and to data processing in geosciences, radar imaging, and structural mechanics.

Explainable AI and Other Applications of Fuzzy Techniques

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Publisher : Springer Nature
ISBN 13 : 3030820998
Total Pages : 506 pages
Book Rating : 4.92/5 ( download)

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Book Synopsis Explainable AI and Other Applications of Fuzzy Techniques by : Julia Rayz

Download or read book Explainable AI and Other Applications of Fuzzy Techniques written by Julia Rayz and published by Springer Nature. This book was released on 2021-07-27 with total page 506 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on an overview of the AI techniques, their foundations, their applications, and remaining challenges and open problems. Many artificial intelligence (AI) techniques do not explain their recommendations. Providing natural-language explanations for numerical AI recommendations is one of the main challenges of modern AI. To provide such explanations, a natural idea is to use techniques specifically designed to relate numerical recommendations and natural-language descriptions, namely fuzzy techniques. This book is of interest to practitioners who want to use fuzzy techniques to make AI applications explainable, to researchers who may want to extend the ideas from these papers to new application areas, and to graduate students who are interested in the state-of-the-art of fuzzy techniques and of explainable AI—in short, to anyone who is interested in problems involving fuzziness and AI in general.