Statistical Modeling Analysis And Management Of Fuzzy Data
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Statistical Modeling Analysis And Management Of Fuzzy Data
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Author : Carlo Bertoluzza
language : en
Publisher: Physica
Release Date : 2012-11-02
Statistical Modeling Analysis And Management Of Fuzzy Data written by Carlo Bertoluzza and has been published by Physica this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-11-02 with Computers categories.
"Statistical Modeling, Analysis and Management of Fuzzy Data," or SMFD for short, is an important contribution to a better understanding of a basic issue -an issue which has been controversial, and still is though to a lesser degree. In substance, the issue is: are fuzziness and randomness distinct or coextensive facets of uncertainty? Are the theories of fuzziness and random ness competitive or complementary? In SMFD, these and related issues are addressed with rigor, authority and insight by prominent contributors drawn, in the main, from probability theory, fuzzy set theory and data analysis com munities. First, a historical perspective. The almost simultaneous births -close to half a century ago-of statistically-based information theory and cybernetics were two major events which marked the beginning of the steep ascent of probability theory and statistics in visibility, influence and importance. I was a student when information theory and cybernetics were born, and what is etched in my memory are the fascinating lectures by Shannon and Wiener in which they sketched their visions of the coming era of machine intelligence and automation of reasoning and decision processes. What I heard in those lectures inspired one of my first papers (1950) "An Extension of Wiener's Theory of Prediction," and led to my life-long interest in probability theory and its applications to information processing, decision analysis and control.
Statistical Modeling Analysis And Management Of Fuzzy Data
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Author : Carlo Bertoluzza
language : en
Publisher:
Release Date : 2014-01-15
Statistical Modeling Analysis And Management Of Fuzzy Data written by Carlo Bertoluzza and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-01-15 with categories.
Soft Methods For Integrated Uncertainty Modelling
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Author : Jonathan Lawry
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-10-08
Soft Methods For Integrated Uncertainty Modelling written by Jonathan Lawry and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-10-08 with Computers categories.
The idea of soft computing emerged in the early 1990s from the fuzzy systems c- munity, and refers to an understanding that the uncertainty, imprecision and ig- rance present in a problem should be explicitly represented and possibly even - ploited rather than either eliminated or ignored in computations. For instance, Zadeh de?ned ‘Soft Computing’ as follows: Soft computing differs from conventional (hard) computing in that, unlike hard computing, it is tolerant of imprecision, uncertainty and partial truth. In effect, the role model for soft computing is the human mind. Recently soft computing has, to some extent, become synonymous with a hybrid approach combining AI techniques including fuzzy systems, neural networks, and biologically inspired methods such as genetic algorithms. Here, however, we adopt a more straightforward de?nition consistent with the original concept. Hence, soft methods are understood as those uncertainty formalisms not part of mainstream s- tistics and probability theory which have typically been developed within the AI and decisionanalysiscommunity.Thesearemathematicallysounduncertaintymodelling methodologies which are complementary to conventional statistics and probability theory.
Soft Methodology And Random Information Systems
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Author : Miguel Concepcion Lopez-Diaz
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-06-05
Soft Methodology And Random Information Systems written by Miguel Concepcion Lopez-Diaz and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-05 with Mathematics categories.
The analysis of experimental data resulting from some underlying random process is a fundamental part of most scientific research. Probability Theory and Statistics have been developed as flexible tools for this analyis, and have been applied successfully in various fields such as Biology, Economics, Engineering, Medicine or Psychology. However, traditional techniques in Probability and Statistics were devised to model only a singe source of uncertainty, namely randomness. In many real-life problems randomness arises in conjunction with other sources, making the development of additional "softening" approaches essential. This book is a collection of papers presented at the 2nd International Conference on Soft Methods in Probability and Statistics (SMPS’2004) held in Oviedo, providing a comprehensive overview of the innovative new research taking place within this emerging field.
Soft Modeling In Industrial Manufacturing
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Author : Przemyslaw Grzegorzewski
language : en
Publisher: Springer
Release Date : 2018-12-11
Soft Modeling In Industrial Manufacturing written by Przemyslaw Grzegorzewski and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-11 with Technology & Engineering categories.
This book discusses the problems of complexity in industrial data, including the problems of data sources, causes and types of data uncertainty, and methods of data preparation for further reasoning in engineering practice. Each data source has its own specificity, and a characteristic property of industrial data is its high degree of uncertainty. The book also explores a wide spectrum of soft modeling methods with illustrations pertaining to specific cases from diverse industrial processes. In soft modeling the physical nature of phenomena may not be known and may not be taken into consideration. Soft models usually employ simplified mathematical equations derived directly from the data obtained as observations or measurements of the given system. Although soft models may not explain the nature of the phenomenon or system under study, they usually point to its significant features or properties.
Soft Methods For Handling Variability And Imprecision
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Author : Didier Dubois
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-10-01
Soft Methods For Handling Variability And Imprecision written by Didier Dubois and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-10-01 with Mathematics categories.
Probability theory has been the only well-founded theory of uncertainty for a long time. It was viewed either as a powerful tool for modelling random phenomena, or as a rational approach to the notion of degree of belief. During the last thirty years, in areas centered around decision theory, artificial intelligence and information processing, numerous approaches extending or orthogonal to the existing theory of probability and mathematical statistics have come to the front. The common feature of those attempts is to allow for softer or wider frameworks for taking into account the incompleteness or imprecision of information. Many of these approaches come down to blending interval or fuzzy interval analysis with probabilistic methods. This book gathers contributions to the 4th International Conference on Soft methods in Probability and Statistics. Its aim is to present recent results illustrating such new trends that enlarge the statistical and uncertainty modeling traditions, towards the handling of incomplete or subjective information. It covers a broad scope ranging from philosophical and mathematical underpinnings of new uncertainty theories, with a stress on their impact in the area of statistics and data analysis, to numerical methods and applications to environmental risk analysis and mechanical engineering. A unique feature of this collection is to establish a dialogue between fuzzy random variables and imprecise probability theories.
Symbolic And Quantitative Approaches To Reasoning With Uncertainty
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Author : Claudio Sossai
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-06-19
Symbolic And Quantitative Approaches To Reasoning With Uncertainty written by Claudio Sossai and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-06-19 with Computers categories.
These are the proceedings of the 10th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty, ECSQARU 2009, held in Verona (Italy), July 1–3, 2009. The biennial ECSQARU conferences are a major forum for advances in the theory and practice of reasoning under uncertainty. The ?rst ECSQARU conf- ence was held in Marseille (1991), and since then it has been held in Granada (1993), Fribourg (1995), Bonn (1997), London (1999), Toulouse (2001), Aalborg (2003), Barcelona (2005) and Hammamet (2007). The 76 papers gathered in this volume were selected out of 118 submissions from 34 countries, after a rigorous review process. In addition, the conference included invited lectures by three outstanding researchers in the area: Isabelle Bloch (“Fuzzy and bipolar mathematical morphology, applications in spatial reasoning”), Petr Cintula (“From (deductive) fuzzy logic to (logic-based) fuzzy mathematics”),andDaniele Mundici(“Conditionalsandindependence inma- valued logics”). Twospecialsessionswerepresentedduringtheconference:“Conditioning,- dependence, inference” (organizedby Giulianella Coletti and BarbaraVantaggi) and “Mathematicalfuzzy logic” (organizedby Stefano Aguzzoli,Brunella Gerla, Llu´ ?s Godo, Vincenzo Marra, Franco Montagna) On the whole, the program of the conference provided a broad, rich and up-to-date perspective of the current high-level research in the area which is re?ected in the contents of this volume.
Statistical Modeling Analysis And Management Of Fuzzy Data
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Author : Carlo Bertoluzza
language : en
Publisher: Physica
Release Date : 2002-01-11
Statistical Modeling Analysis And Management Of Fuzzy Data written by Carlo Bertoluzza and has been published by Physica this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002-01-11 with Computers categories.
The contributions in this book state the complementary rather than competitive relationship between Probability and Fuzzy Set Theory and allow solutions to real life problems with suitable combinations of both theories.
Towards A Unified Modeling And Knowledge Representation Based On Lattice Theory
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Author : Vassilis G. Kaburlasos
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-02-07
Towards A Unified Modeling And Knowledge Representation Based On Lattice Theory written by Vassilis G. Kaburlasos and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-02-07 with Computers categories.
This research monograph proposes a unified, cross-fertilizing approach for knowledge-representation and modeling based on lattice theory. The emphasis is on clustering, classification, and regression applications. It presents novel tools and useful perspectives for effective pattern classification. The material is multi-disciplinary based on on-going research published in major scientific journals and conferences.
Evolving Rule Based Models
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Author : Plamen P. Angelov
language : en
Publisher: Physica
Release Date : 2013-03-20
Evolving Rule Based Models written by Plamen P. Angelov and has been published by Physica this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-20 with Mathematics categories.
The idea about this book has evolved during the process of its preparation as some of the results have been achieved in parallel with its writing. One reason for this is that in this area of research results are very quickly updated. Another is, possibly, that a strong, unchallenged theoretical basis in this field still does not fully exist. From other hand, the rate of innovation, competition and demand from different branches of industry (from biotech industry to civil and building engineering, from market forecasting to civil aviation, from robotics to emerging e-commerce) is increasingly pressing for more customised solutions based on learning consumers behaviour. A highly interdisciplinary and rapidly innovating field is forming which focus is the design of intelligent, self-adapting systems and machines. It is on the crossroads of control theory, artificial and computational intelligence, different engineering disciplines borrowing heavily from the biology and life sciences. It is often called intelligent control, soft computing or intelligent technology. Some other branches have appeared recently like intelligent agents (which migrated from robotics to different engineering fields), data fusion, knowledge extraction etc., which are inherently related to this field. The core is the attempts to enhance the abilities of the classical control theory in order to have more adequate, flexible, and adaptive models and control algorithms.