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Author: Carlo Bertoluzza
Publisher: Physica
Published: 2012-11-02
Total Pages: 315
ISBN-13: 3790818003
DOWNLOAD EBOOK →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.
Author: Reinhard Viertl
Publisher: John Wiley & Sons
Published: 2011-01-25
Total Pages: 199
ISBN-13: 0470974567
DOWNLOAD EBOOK →Statistical data are not always precise numbers, or vectors, or categories. Real data are frequently what is called fuzzy. Examples where this fuzziness is obvious are quality of life data, environmental, biological, medical, sociological and economics data. Also the results of measurements can be best described by using fuzzy numbers and fuzzy vectors respectively. Statistical analysis methods have to be adapted for the analysis of fuzzy data. In this book, the foundations of the description of fuzzy data are explained, including methods on how to obtain the characterizing function of fuzzy measurement results. Furthermore, statistical methods are then generalized to the analysis of fuzzy data and fuzzy a-priori information. Key Features: Provides basic methods for the mathematical description of fuzzy data, as well as statistical methods that can be used to analyze fuzzy data. Describes methods of increasing importance with applications in areas such as environmental statistics and social science. Complements the theory with exercises and solutions and is illustrated throughout with diagrams and examples. Explores areas such quantitative description of data uncertainty and mathematical description of fuzzy data. This work is aimed at statisticians working with fuzzy logic, engineering statisticians, finance researchers, and environmental statisticians. It is written for readers who are familiar with elementary stochastic models and basic statistical methods.
Author: Rédina Berkachy
Publisher: Springer Nature
Published: 2021-10-31
Total Pages: 356
ISBN-13: 303076916X
DOWNLOAD EBOOK →The main focus of this book is on presenting advances in fuzzy statistics, and on proposing a methodology for testing hypotheses in the fuzzy environment based on the estimation of fuzzy confidence intervals, a context in which not only the data but also the hypotheses are considered to be fuzzy. The proposed method for estimating these intervals is based on the likelihood method and employs the bootstrap technique. A new metric generalizing the signed distance measure is also developed. In turn, the book presents two conceptually diverse applications in which defended intervals play a role: one is a novel methodology for evaluating linguistic questionnaires developed at the global and individual levels; the other is an extension of the multi-ways analysis of variance to the space of fuzzy sets. To illustrate these approaches, the book presents several empirical and simulation-based studies with synthetic and real data sets. In closing, it presents a coherent R package called “FuzzySTs” which covers all the previously mentioned concepts with full documentation and selected use cases. Given its scope, the book will be of interest to all researchers whose work involves advanced fuzzy statistical methods.
Author: Graeme D Hutcheson
Publisher: SAGE
Published: 2008-02-12
Total Pages: 255
ISBN-13: 1849202486
DOWNLOAD EBOOK →Bringing to life the most widely used quantitative measurements and statistical techniques in marketing, this book is packed with user-friendly descriptions, examples and study applications. The process of making marketing decisions is frequently dependent on quantitative analysis and the use of specific statistical tools and techniques which can be tailored and adapted to solve particular marketing problems. Any student hoping to enter the world of marketing will need to show that they understand and have mastered these techniques. A bank of downloadable data sets to compliment the tables provided in the textbook are provided free for you.
Author: Wang, John
Publisher: IGI Global
Published: 2005-06-30
Total Pages: 1382
ISBN-13: 1591405599
DOWNLOAD EBOOK →Data Warehousing and Mining (DWM) is the science of managing and analyzing large datasets and discovering novel patterns and in recent years has emerged as a particularly exciting and industrially relevant area of research. Prodigious amounts of data are now being generated in domains as diverse as market research, functional genomics and pharmaceuticals; intelligently analyzing these data, with the aim of answering crucial questions and helping make informed decisions, is the challenge that lies ahead. The Encyclopedia of Data Warehousing and Mining provides a comprehensive, critical and descriptive examination of concepts, issues, trends, and challenges in this rapidly expanding field of data warehousing and mining (DWM). This encyclopedia consists of more than 350 contributors from 32 countries, 1,800 terms and definitions, and more than 4,400 references. This authoritative publication offers in-depth coverage of evolutions, theories, methodologies, functionalities, and applications of DWM in such interdisciplinary industries as healthcare informatics, artificial intelligence, financial modeling, and applied statistics, making it a single source of knowledge and latest discoveries in the field of DWM.
Author: Zhenyuan Wang
Publisher: Springer Science & Business Media
Published: 2010-07-07
Total Pages: 392
ISBN-13: 0387768521
DOWNLOAD EBOOK →Generalized Measure Theory examines the relatively new mathematical area of generalized measure theory. The exposition unfolds systematically, beginning with preliminaries and new concepts, followed by a detailed treatment of important new results regarding various types of nonadditive measures and the associated integration theory. The latter involves several types of integrals: Sugeno integrals, Choquet integrals, pan-integrals, and lower and upper integrals. All of the topics are motivated by numerous examples, culminating in a final chapter on applications of generalized measure theory. Some key features of the book include: many exercises at the end of each chapter along with relevant historical and bibliographical notes, an extensive bibliography, and name and subject indices. The work is suitable for a classroom setting at the graduate level in courses or seminars in applied mathematics, computer science, engineering, and some areas of science. A sound background in mathematical analysis is required. Since the book contains many original results by the authors, it will also appeal to researchers working in the emerging area of generalized measure theory.
Author: Cengiz Kahraman
Publisher: Springer
Published: 2016-07-15
Total Pages: 356
ISBN-13: 3319390147
DOWNLOAD EBOOK →This book offers a comprehensive reference guide to fuzzy statistics and fuzzy decision-making techniques. It provides readers with all the necessary tools for making statistical inference in the case of incomplete information or insufficient data, where classical statistics cannot be applied. The respective chapters, written by prominent researchers, explain a wealth of both basic and advanced concepts including: fuzzy probability distributions, fuzzy frequency distributions, fuzzy Bayesian inference, fuzzy mean, mode and median, fuzzy dispersion, fuzzy p-value, and many others. To foster a better understanding, all the chapters include relevant numerical examples or case studies. Taken together, they form an excellent reference guide for researchers, lecturers and postgraduate students pursuing research on fuzzy statistics. Moreover, by extending all the main aspects of classical statistical decision-making to its fuzzy counterpart, the book presents a dynamic snapshot of the field that is expected to stimulate new directions, ideas and developments.
Author: Joao Paulo Carvalho
Publisher: Springer
Published: 2016-06-10
Total Pages: 836
ISBN-13: 3319405810
DOWNLOAD EBOOK →This two volume set (CCIS 610 and 611) constitute the proceedings of the 16th International Conference on Information processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2016, held in Eindhoven, The Netherlands, in June 2016. The 127 revised full papers presented together with four invited talks were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on fuzzy measures and integrals; uncertainty quantification with imprecise probability; textual data processing; belief functions theory and its applications; graphical models; fuzzy implications functions; applications in medicine and bioinformatics; real-world applications; soft computing for image processing; clustering; fuzzy logic, formal concept analysis and rough sets; graded and many-valued modal logics; imperfect databases; multiple criteria decision methods; argumentation and belief revision; databases and information systems; conceptual aspects of data aggregation and complex data fusion; fuzzy sets and fuzzy logic; decision support; comparison measures; machine learning; social data processing; temporal data processing; aggregation.
Author: Przemyslaw Grzegorzewski
Publisher: Springer Science & Business Media
Published: 2013-12-11
Total Pages: 372
ISBN-13: 3790817732
DOWNLOAD EBOOK →Classical probability theory and mathematical statistics appear sometimes too rigid for real life problems, especially while dealing with vague data or imprecise requirements. These problems have motivated many researchers to "soften" the classical theory. Some "softening" approaches utilize concepts and techniques developed in theories such as fuzzy sets theory, rough sets, possibility theory, theory of belief functions and imprecise probabilities, etc. Since interesting mathematical models and methods have been proposed in the frameworks of various theories, this text brings together experts representing different approaches used in soft probability, statistics and data analysis.
Author: Jonathan Lawry
Publisher: Springer Science & Business Media
Published: 2007-10-08
Total Pages: 413
ISBN-13: 3540347771
DOWNLOAD EBOOK →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.
