Fusion of qualitative beliefs

Fusion of qualitative beliefs

Author: Florentin Smarandache

Publisher: Infinite Study

Published:

Total Pages: 18

ISBN-13:

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This chapter introduces the notion of qualitative belief assignment to model beliefs of human experts expressed in natural language (with linguistic labels). We show how qualitative beliefs can be efficiently combined using an extension of Dezert-Smarandache Theory (DSmT) of plausible and paradoxical quantitative reasoning to qualitative reasoning.


General Combination Rules for Qualitative and Quantitative Beliefs

General Combination Rules for Qualitative and Quantitative Beliefs

Author: ARNAUD MARTIN

Publisher: Infinite Study

Published:

Total Pages: 23

ISBN-13:

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Martin and Osswald have recently proposed many generalizations of combination rules on quantitative beliefs in order to manage the conflict and to consider the specificity of the responses of the experts. Since the experts express themselves usually in natural language with linguistic labels, Smarandache and Dezert have introduced a mathematical framework for dealing directly also with qualitative beliefs. In this paper we recall some element of our previous works and propose the new combination rules, developed for the fusion of both qualitative or quantitative beliefs.


Fusion of imprecise qualitative information

Fusion of imprecise qualitative information

Author: Xinde Li

Publisher: Infinite Study

Published:

Total Pages: 12

ISBN-13:

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In this paper, we present a new 2-tuple linguistic representation model, i.e. Distribution Function Model (DFM), for combining imprecise qualitative information using fusion rules drawn from Dezert-Smarandache Theory (DSmT) framework.


Qualitative Belief Conditioning Rules (QBCR)

Qualitative Belief Conditioning Rules (QBCR)

Author: Florentin Smarandache

Publisher: Infinite Study

Published:

Total Pages: 13

ISBN-13:

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In this paper we extend the new family of (quantitative) Belief Conditioning Rules (BCR) recently developed in the Dezert-Smarandache Theory (DSmT) to their qualitative counterpart for belief revision.


An introduction to DSmT

An introduction to DSmT

Author: Jean Dezert

Publisher: Infinite Study

Published:

Total Pages: 72

ISBN-13:

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The management and combination of uncertain, imprecise, fuzzy and even paradoxical or highly conflicting sources of information has always been, and still remains today, of primal importance for the development of reliable modern information systems involving artificial reasoning.


Rough Sets and Current Trends in Computing

Rough Sets and Current Trends in Computing

Author: Shusaku Tsumoto

Publisher: Springer Science & Business Media

Published: 2004-05-21

Total Pages: 871

ISBN-13: 3540221174

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In recent years rough set theory has attracted the attention of many researchers and practitioners all over the world, who have contributed essentially to its development and applications. Weareobservingagrowingresearchinterestinthefoundationsofroughsets, including the various logical, mathematical and philosophical aspects of rough sets. Some relationships have already been established between rough sets and other approaches, and also with a wide range of hybrid systems. As a result, rough sets are linked with decision system modeling and analysis of complex systems, fuzzy sets, neural networks, evolutionary computing, data mining and knowledge discovery, pattern recognition, machine learning, and approximate reasoning. In particular, rough sets are used in probabilistic reasoning, granular computing (including information granule calculi based on rough mereology), intelligent control, intelligent agent modeling, identi?cation of autonomous s- tems, and process speci?cation. Methods based on rough set theory alone or in combination with other - proacheshavebeendiscoveredwith awide rangeofapplicationsinsuchareasas: acoustics, bioinformatics, business and ?nance, chemistry, computer engineering (e.g., data compression, digital image processing, digital signal processing, p- allel and distributed computer systems, sensor fusion, fractal engineering), de- sion analysis and systems, economics, electrical engineering (e.g., control, signal analysis, power systems), environmental studies, informatics, medicine, mole- lar biology, musicology, neurology, robotics, social science, software engineering, spatial visualization, Web engineering, and Web mining.


DSm field and linear algebra of refined labels

DSm field and linear algebra of refined labels

Author: Florentin Smarandache

Publisher: Infinite Study

Published:

Total Pages: 11

ISBN-13:

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This chapter presents the DSm Field and Linear Algebra of Refined Labels (FLARL) in DSmT framework in order to work precisely with qualitative labels for information fusion. We present and justify the basic operators on qualitative labels (addition, subtraction, multiplication, division, root, power, etc).


Multispace & Multistructure. Neutrosophic Transdisciplinarity (100 Collected Papers of Science)

Multispace & Multistructure. Neutrosophic Transdisciplinarity (100 Collected Papers of Science)

Author: Florentin Smarandache

Publisher: Infinite Study

Published: 2010

Total Pages: 802

ISBN-13: 9526734920

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This is an eclectic tome of 100 papers in various fields of sciences, alphabetically listed, such as: astronomy, biology, calculus, chemistry, computer programming codification, economics and business and politics, education and administration, game theory, geometry, graph theory,information fusion, neutrosophic logic and set, non-Euclidean geometry, number theory, paradoxes, philosophy of science, psychology, quantum physics, scientific research methods, and statistics ¿ containing 800 pages.It was my preoccupation and collaboration as author, co-author, translator, or co-translator, and editor with many scientists from around the world for long time. Many ideas from this book are to be developed and expanded in future explorations.