Download or read book Performance Measurement with Fuzzy Data Envelopment Analysis written by Ali Emrouznejad and published by Springer. This book was released on 2013-11-29 with total page 293 pages. Available in PDF, EPUB and Kindle. Book excerpt: The intensity of global competition and ever-increasing economic uncertainties has led organizations to search for more efficient and effective ways to manage their business operations. Data envelopment analysis (DEA) has been widely used as a conceptually simple yet powerful tool for evaluating organizational productivity and performance. Fuzzy DEA (FDEA) is a promising extension of the conventional DEA proposed for dealing with imprecise and ambiguous data in performance measurement problems. This book is the first volume in the literature to present the state-of-the-art developments and applications of FDEA. It is designed for students, educators, researchers, consultants and practicing managers in business, industry, and government with a basic understanding of the DEA and fuzzy logic concepts.

Download or read book Statistical Methods for Fuzzy Data written by Reinhard Viertl and published by John Wiley & Sons. This book was released on 2011-01-25 with total page 199 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Fuzzy Cluster Analysis written by Frank Höppner and published by John Wiley & Sons. This book was released on 1999-07-09 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dieser Band konzentriert sich auf Konzepte, Algorithmen und Anwendungen des Fuzzy Clustering. In sich geschlossen werden Techniken wie das Fuzzy-c-Mittel und die Gustafson-Kessel- und Gath- und Gava-Algorithmen behandelt, wobei vom Leser keine Vorkenntnisse auf dem Gebiet von Fuzzy-Systemen erwartet werden. Durch anschauliche Anwendungsbeispiele eignet sich das Buch als Einführung für Praktiker der Datenanalyse, der Bilderkennung und der angewandten Mathematik. (05/99)

Download or read book Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making written by Cengiz Kahraman and published by Springer. This book was released on 2019-07-05 with total page 1392 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes the proceedings of the Intelligent and Fuzzy Techniques INFUS 2019 Conference, held in Istanbul, Turkey, on July 23–25, 2019. Big data analytics refers to the strategy of analyzing large volumes of data, or big data, gathered from a wide variety of sources, including social networks, videos, digital images, sensors, and sales transaction records. Big data analytics allows data scientists and various other users to evaluate large volumes of transaction data and other data sources that traditional business systems would be unable to tackle. Data-driven and knowledge-driven approaches and techniques have been widely used in intelligent decision-making, and they are increasingly attracting attention due to their importance and effectiveness in addressing uncertainty and incompleteness. INFUS 2019 focused on intelligent and fuzzy systems with applications in big data analytics and decision-making, providing an international forum that brought together those actively involved in areas of interest to data science and knowledge engineering. These proceeding feature about 150 peer-reviewed papers from countries such as China, Iran, Turkey, Malaysia, India, USA, Spain, France, Poland, Mexico, Bulgaria, Algeria, Pakistan, Australia, Lebanon, and Czech Republic.

Download or read book Fundamentals of Statistics with Fuzzy Data written by Hung T. Nguyen and published by Springer. This book was released on 2006-02-28 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents basic aspects for a theory of statistics with fuzzy data, together with a set of practical applications. Theories of fuzzy logic and of random closed sets are used as basic ingredients in building statistical concepts and procedures in the context of imprecise data, including coarse data analysis. The book aims at motivating statisticians to examine fuzzy statistics to enlarge the domain of applicability of statistics in general.

Download or read book Data Engineering written by Olaf Wolkenhauer and published by John Wiley & Sons. This book was released on 2004-04-07 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although data engineering is a multi-disciplinary field withapplications in control, decision theory, and the emerging hot areaof bioinformatics, there are no books on the market that make thesubject accessible to non-experts. This book fills the gap in thefield, offering a clear, user-friendly introduction to the maintheoretical and practical tools for analyzing complex systems. Anftp site features the corresponding MATLAB and Mathematical toolsand simulations. Market: Researchers in data management, electrical engineering,computer science, and life sciences.

Download or read book Fuzzy Data Analysis written by Hans Bandemer and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 351 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fuzzy data such as marks, scores, verbal evaluations, imprecise observations, experts' opinions and grey tone pictures, are quite common. In Fuzzy Data Analysis the authors collect their recent results providing the reader with ideas, approaches and methods for processing such data when looking for sub-structures in knowledge bases for an evaluation of functional relationship, e.g. in order to specify diagnostic or control systems. The modelling presented uses ideas from fuzzy set theory and the suggested methods solve problems usually tackled by data analysis if the data are real numbers. Fuzzy Data Analysis is self-contained and is addressed to mathematicians oriented towards applications and to practitioners in any field of application who have some background in mathematics and statistics.

Download or read book Fuzzy Sets in Decision Analysis Operations Research and Statistics written by Roman Slowiński and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 467 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fuzzy Sets in Decision Analysis, Operations Research and Statistics includes chapters on fuzzy preference modeling, multiple criteria analysis, ranking and sorting methods, group decision-making and fuzzy game theory. It also presents optimization techniques such as fuzzy linear and non-linear programming, applications to graph problems and fuzzy combinatorial methods such as fuzzy dynamic programming. In addition, the book also accounts for advances in fuzzy data analysis, fuzzy statistics, and applications to reliability analysis. These topics are covered within four parts: Decision Making, Mathematical Programming, Statistics and Data Analysis, and Reliability, Maintenance and Replacement. The scope and content of the book has resulted from multiple interactions between the editor of the volume, the series editors, the series advisory board, and experts in each chapter area. Each chapter was written by a well-known researcher on the topic and reviewed by other experts in the area. These expert reviewers sometimes became co-authors because of the extent of their contribution to the chapter. As a result, twenty-five authors from twelve countries and four continents were involved in the creation of the 13 chapters, which enhances the international character of the project and gives an idea of how carefully the Handbook has been developed.

Download or read book Scalable Fuzzy Algorithms for Data Management and Analysis Methods and Design written by Laurent, Anne and published by IGI Global. This book was released on 2009-10-31 with total page 466 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book presents up-to-date techniques for addressing data management problems with logic and memory use"--Provided by publisher.

Download or read book Fuzzy Data Analysis written by Hans Bandemer and published by . This book was released on 1992-06-30 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fuzzy data such as marks, scores, verbal evaluations, imprecise observations, experts' opinions and grey tone pictures, are quite common. In Fuzzy Data Analysis the authors collect their recent results providing the reader with ideas, approaches and methods for processing such data when looking for sub-structures in knowledge bases for an evaluation of functional relationship, e.g. in order to specify diagnostic or control systems. The modelling presented uses ideas from fuzzy set theory and the suggested methods solve problems usually tackled by data analysis if the data are real numbers. Fuzzy Data Analysis is self-contained and is addressed to mathematicians oriented towards applications and to practitioners in any field of application who have some background in mathematics and statistics.

Download or read book Statistical Modeling Analysis and Management of Fuzzy Data written by Carlo Bertoluzza and published by Physica. This book was released on 2012-11-02 with total page 315 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Fuzzy System and Data Mining written by Gang Chen and published by . This book was released on 2016 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fuzzy logic is widely used in machine control. The term 'fuzzy' refers to the fact that the logic involved can deal with concepts that cannot be expressed as either 'true' or 'false', but rather as 'partially true'. Fuzzy set theory is very suitable for modeling the uncertain duration in process simulation, as well as defining the fuzzy goals and fuzzy constraints of decision-making. It has many applications in industry, engineering and social sciences.This book presents the proceedings of the 2015 International Conference on Fuzzy Systems and Data Mining (FSDM2015), held in Shanghai, China, in December 2015. The application domain covers geography, biology, economics, medicine, the energy industry, social science, logistics, transport, industrial and production engineering, and computer science. The papers presented at the conference focus on topics such as system diagnosis, rule induction, process simulation/control, and decision-making. They include papers on solving practical problems with intelligent algorithms; statistical analysis; classification and clustering; and association rule learning. They also reflect the frontier in data mining research and address the challenges posed to data analytics research by the increasingly large datasets yielded by many application domains, together with new types of unstructured data.The book provides an overview of the ways in which fuzzy theory and data mining principles are applied in various fields, and will be of interest to all those who work in either the theory or practice of fuzzy systems and data mining.

Download or read book Applications of Fuzzy Sets to Systems Analysis written by NEGOITA and published by Birkhäuser. This book was released on 2013-12-11 with total page 189 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ten years ago, Zadeh has brought into vogue the use of a name. Scientists no is an increasing less than poets strike off words that fit a situation. Today there recognition that for understanding vagueness, a fuzzy approach is required. We are just going through ~ transient period. From discussions of general philosophy to practical methods for system analysis. Unfortunately, much of the existing research is scattered. The practitioner interested in these methods face the challenge of sorting through a vast amount of literature to find a core on which to build. One of the objects of this book was to facilitate communication by bringing toge ther different viewpoints and coloring them from a common viewpoint. Since the romanian version appeared, at the very beginning of 1974, there has been a rapid growth in the literature of fuzzy modelling. A minor revision would have left the book quite out-of-date. The opportunity has been taken to correct, clarify, and update. Inexactness is implicit in human behaviour and erare humanum est. It is a pleasure to acknowledge the help we have received in preparing this version. The opportunity to see an english edition was a powerful stimulus, and we are grateful to Salomon Klaczko for making this possible. Another debt is to all fuzzy authors we have quoted. Their fascinating papers kindled our interest in the subject.

Download or read book Fuzzy Set Social Science written by Charles C. Ragin and published by University of Chicago Press. This book was released on 2000-08 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this innovative approach to the practice of social scienceÇharles Ragin explores the use of fuzzy sets to bridge the divide between quantitive and qualitative methods. He argues that fuzzy sets allow a far richer dialogue between ideas and evidence in social research than previously possible.

Download or read book Fuzzy Sets in Information Retrieval and Cluster Analysis written by S. Miyamoto and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: The present monograph intends to establish a solid link among three fields: fuzzy set theory, information retrieval, and cluster analysis. Fuzzy set theory supplies new concepts and methods for the other two fields, and provides a common frame work within which they can be reorganized. Four principal groups of readers are assumed: researchers or students who are interested in (a) application of fuzzy sets, (b) theory of information retrieval or bibliographic databases, (c) hierarchical clustering, and (d) application of methods in systems science. Readers in group (a) may notice that the fuzzy set theory used here is very simple, since only finite sets are dealt with. This simplification enables the max min algebra to deal with fuzzy relations and matrices as equivalent entities. Fuzzy graphs are also used for describing theoretical properties of fuzzy relations. This assumption of finite sets is sufficient for applying fuzzy sets to information retrieval and cluster analysis. This means that little theory, beyond the basic theory of fuzzy sets, is required. Although readers in group (b) with little background in the theory of fuzzy sets may have difficulty with a few sections, they will also find enough in this monograph to support an intuitive grasp of this new concept of fuzzy information retrieval. Chapter 4 provides fuzzy retrieval without the use of mathematical symbols. Also, fuzzy graphs will serve as an aid to the intuitive understanding of fuzzy relations.

Download or read book Fundamentals of Statistics with Fuzzy Data written by Hung T. Nguyen and published by Studies in Fuzziness and Soft Computing. This book was released on 2006-03-20 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents basic aspects for a theory of statistics with fuzzy data, together with a set of practical applications. Theories of fuzzy logic and of random closed sets are used as basic ingredients in building statistical concepts and procedures in the context of imprecise data, including coarse data analysis. The book aims at motivating statisticians to examine fuzzy statistics to enlarge the domain of applicability of statistics in general.

Download or read book Computational Science ICCS 2001 written by Vassil Alexandrov and published by Springer Science & Business Media. This book was released on 2001-05-24 with total page 1068 pages. Available in PDF, EPUB and Kindle. Book excerpt: LNCS volumes 2073 and 2074 contain the proceedings of the International Conference on Computational Science, ICCS 2001, held in San Francisco, California, May 27-31, 2001. The two volumes consist of more than 230 contributed and invited papers that reflect the aims of the conference to bring together researchers and scientists from mathematics and computer science as basic computing disciplines, researchers from various application areas who are pioneering advanced application of computational methods to sciences such as physics, chemistry, life sciences, and engineering, arts and humanitarian fields, along with software developers and vendors, to discuss problems and solutions in the area, to identify new issues, and to shape future directions for research, as well as to help industrial users apply various advanced computational techniques.