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Fuzzy Regression Analysis


Fuzzy Regression Analysis
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Fuzzy Regression Analysis


Fuzzy Regression Analysis
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Author : Janusz Kacprzyk
language : en
Publisher: Physica
Release Date : 1992-08-27

Fuzzy Regression Analysis written by Janusz Kacprzyk and has been published by Physica this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992-08-27 with Business & Economics categories.


Regression analysis is a relatively simple yet extremely useful and widely employed tool for determining relationship between some variables on the basis of some observed values taken by these variables. Fuzzy regression analysis has been recently deviced to accomodate in the framework of regression analysis vaguely specified data which are omnipresent in many applications, notably in all areas where human judgements are used. Fuzzy sets theory provides here proper tools. This book is a collection of papers written by virtually all major contributors to fuzzy regression. Its main issue is that vague, imprecise, etc. data may now be used in regression analysis. This is new. Apart from this it gives an extensive coverage of the whole field of fuzzy regression, both in a strictly mathematical and applicational perspective. Most approaches are algorithmic, and can be readily implemented. Information on software is provided.



Fuzzy Sets In Decision Analysis Operations Research And Statistics


Fuzzy Sets In Decision Analysis Operations Research And Statistics
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Author : Roman Slowiński
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Fuzzy Sets In Decision Analysis Operations Research And Statistics written by Roman Slowiński 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 2012-12-06 with Mathematics categories.


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.



Fuzzy Applications In Industrial Engineering


Fuzzy Applications In Industrial Engineering
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Author : Cengiz Kahraman
language : en
Publisher: Springer
Release Date : 2007-05-31

Fuzzy Applications In Industrial Engineering written by Cengiz Kahraman and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-05-31 with Technology & Engineering categories.


Industrial Engineering (IE) is concerned with the design, improvement, and installation of integrated systems of people, material, equipment, and energy. Industrial engineers face many problems with incomplete and vague information in these systems since the characteristics of these problems often require this kind of information. Fuzzy sets approaches are usually most appropriate when human evaluations and the modeling of human knowledge are needed. IE brings a significant number of applications of fuzzy set theory. After an introductory chapter explaining the recent status of fuzzy sets in IE, this volume involves application chapters on the major seven areas of IE to which fuzzy set theory can contribute. These major application areas are Control and Reliability, Engineering Economics and Investment Analysis, Group and Multi-criteria Decision-making, Human Factors Engineering and Ergonomics, Manufacturing Systems and Technology Management, Optimization Techniques, and Statistical Decision-making. Under these major areas, every chapter includes didactic numerical applications. The authors Among many authors in this book, some examples are H.-J. Zimmermann, Janusz Kacprzyk, Hideo Tanaka, Waldemar Karwowski, F. Herrera, C. Kolski, P. Paul Wang, E. Herrera-Viedma, Hung T. Nguyen, Vladik Kreinovich, Jose L. Verdegay, Tomoe Entani, Nikos Tsourveloudis, F. Jimenez.



Optimal Models And Methods With Fuzzy Quantities


Optimal Models And Methods With Fuzzy Quantities
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Author : Bing-Yuan Cao
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-02

Optimal Models And Methods With Fuzzy Quantities written by Bing-Yuan Cao 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 2010-02 with Computers categories.


The book contains ten chapters as follows, Prepare Knowledge, Regression and Self-regression Models with Fuzzy Coefficients; Regression and Self-regression Models with Fuzzy Variables, Fuzzy Input/output Model, Fuzzy Cluster Analysis and Fuzzy Recognition, Fuzzy Linear Programming, Fuzzy Geometric Programming, Fuzzy Relative Equation and Its Optimizing, Interval and Fuzzy Differential Equations and Interval and Fuzzy Functional and Their Variation. It can not only be used as teaching materials or reference books for under-graduates in higher education, master graduates and doctor graduates in the courses of applied mathematics, computer science, artificial intelligence, fuzzy information process and automation, operations research, system science and engineering, and the like, but also serves as a reference book for researchers in these fields, particularly, for researchers in soft science.



Ridge Fuzzy Regression Modelling For Solving Multicollinearity


Ridge Fuzzy Regression Modelling For Solving Multicollinearity
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Author : Hyoshin Kim
language : en
Publisher: Infinite Study
Release Date :

Ridge Fuzzy Regression Modelling For Solving Multicollinearity written by Hyoshin Kim and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on with Mathematics categories.


This paper proposes an a-level estimation algorithm for ridge fuzzy regression modeling, addressing the multicollinearity phenomenon in the fuzzy linear regression setting.



Uncertainty Modeling And Analysis In Civil Engineering


Uncertainty Modeling And Analysis In Civil Engineering
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Author : Bilal M. Ayyub
language : en
Publisher: CRC Press
Release Date : 1997-12-29

Uncertainty Modeling And Analysis In Civil Engineering written by Bilal M. Ayyub and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997-12-29 with Technology & Engineering categories.


With the expansion of new technologies, materials, and the design of complex systems, the expectations of society upon engineers are becoming larger than ever. Engineers make critical decisions with potentially high adverse consequences. The current political, societal, and financial climate requires engineers to formally consider the factors of uncertainty (e.g., floods, earthquakes, winds, environmental risks) in their decisions at all levels. Uncertainty Modeling and Analysis in Civil Engineering provides a thorough report on the immediate state of uncertainty modeling and analytical methods for civil engineering systems, presenting a toolbox for solving problems in real-world situations. Topics include Neural networks Genetic algorithms Numerical modeling Fuzzy sets and operations Reliability and risk analysis Systems control Uncertainty in probability estimates This compendium is a considerable reference for civil engineers as well as for engineers in other disciplines, computer scientists, general scientists, and students.



Analysis Of Socio Economic Conditions


Analysis Of Socio Economic Conditions
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Author : Gianni Betti
language : en
Publisher: Routledge
Release Date : 2021-03-22

Analysis Of Socio Economic Conditions written by Gianni Betti and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-22 with Business & Economics categories.


Showcasing fuzzy set theory, this book highlights the enormous potential of fuzzy logic in helping to analyse the complexity of a wide range of socio-economic patterns and behaviour. The contributions to this volume explore the most up-to-date fuzzy-set methods for the measurement of socio-economic phenomena in a multidimensional and/or dynamic perspective. Thus far, fuzzy-set theory has primarily been utilised in the social sciences in the field of poverty measurement. These chapters examine the latest work in this area, while also exploring further applications including social exclusion, the labour market, educational mismatch, sustainability, quality of life and violence against women. The authors demonstrate that real-world situations are often characterised by imprecision, uncertainty and vagueness, which cannot be properly described by the classical set theory which uses a simple true–false binary logic. By contrast, fuzzy-set theory has been shown to be a powerful tool for describing the multidimensionality and complexity of social phenomena. This book will be of significant interest to economists, statisticians and sociologists utilising quantitative methods to explore socio-economic phenomena.



Fuzzy Regression Analysis


Fuzzy Regression Analysis
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Author : J. Kacprzyk
language : en
Publisher:
Release Date : 1992-08-01

Fuzzy Regression Analysis written by J. Kacprzyk and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992-08-01 with categories.




Data Engineering


Data Engineering
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Author : Olaf Wolkenhauer
language : en
Publisher: John Wiley & Sons
Release Date : 2004-04-07

Data Engineering written by Olaf Wolkenhauer and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-04-07 with Technology & Engineering categories.


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.



Fuzzy Statistics


Fuzzy Statistics
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Author : James J. Buckley
language : en
Publisher: Springer
Release Date : 2013-11-11

Fuzzy Statistics written by James J. Buckley and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-11-11 with Technology & Engineering categories.


1. 1 Introduction This book is written in four major divisions. The first part is the introductory chapters consisting of Chapters 1 and 2. In part two, Chapters 3-11, we develop fuzzy estimation. For example, in Chapter 3 we construct a fuzzy estimator for the mean of a normal distribution assuming the variance is known. More details on fuzzy estimation are in Chapter 3 and then after Chapter 3, Chapters 4-11 can be read independently. Part three, Chapters 12- 20, are on fuzzy hypothesis testing. For example, in Chapter 12 we consider the test Ho : /1 = /10 verses HI : /1 f=- /10 where /1 is the mean of a normal distribution with known variance, but we use a fuzzy number (from Chapter 3) estimator of /1 in the test statistic. More details on fuzzy hypothesis testing are in Chapter 12 and then after Chapter 12 Chapters 13-20 may be read independently. Part four, Chapters 21-27, are on fuzzy regression and fuzzy prediction. We start with fuzzy correlation in Chapter 21. Simple linear regression is the topic in Chapters 22-24 and Chapters 25-27 concentrate on multiple linear regression. Part two (fuzzy estimation) is used in Chapters 22 and 25; and part 3 (fuzzy hypothesis testing) is employed in Chapters 24 and 27. Fuzzy prediction is contained in Chapters 23 and 26. A most important part of our models in fuzzy statistics is that we always start with a random sample producing crisp (non-fuzzy) data.