Fuzzy Regression Analysis

Fuzzy Regression Analysis PDF Author: Janusz Kacprzyk
Publisher: Physica
ISBN:
Category : Business & Economics
Languages : en
Pages : 302

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Book Description
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 Regression Analysis

Fuzzy Regression Analysis PDF Author: Janusz Kacprzyk
Publisher: Physica
ISBN:
Category : Business & Economics
Languages : en
Pages : 302

Get Book Here

Book Description
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 PDF Author: Roman SlowiƄski
Publisher: Springer Science & Business Media
ISBN: 1461556457
Category : Mathematics
Languages : en
Pages : 467

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Book Description
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 Regression Analysis

Fuzzy Regression Analysis PDF Author: J. Kacprzyk
Publisher:
ISBN: 9780387914350
Category :
Languages : en
Pages : 279

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Book Description


Fuzzy Applications in Industrial Engineering

Fuzzy Applications in Industrial Engineering PDF Author: Cengiz Kahraman
Publisher: Springer
ISBN: 354033517X
Category : Technology & Engineering
Languages : en
Pages : 609

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Book Description
After an introductory chapter explaining recent applications of fuzzy sets in IE, this book explores the seven major areas of IE to which fuzzy set theory can contribute: 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.

Ridge Fuzzy Regression Modelling for Solving Multicollinearity

Ridge Fuzzy Regression Modelling for Solving Multicollinearity PDF Author: Hyoshin Kim
Publisher: Infinite Study
ISBN:
Category : Mathematics
Languages : en
Pages : 15

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

Optimal Models and Methods with Fuzzy Quantities

Optimal Models and Methods with Fuzzy Quantities PDF Author: Bing-Yuan Cao
Publisher: Springer Science & Business Media
ISBN: 3642107109
Category : Computers
Languages : en
Pages : 383

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Book Description
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.

Fuzzy Regression Analysis

Fuzzy Regression Analysis PDF Author: Ping-Teng Chang
Publisher:
ISBN:
Category :
Languages : en
Pages : 154

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Book Description


Conventional and Fuzzy Regression

Conventional and Fuzzy Regression PDF Author: Vlassios Hrissanthou
Publisher: Nova Science Publishers
ISBN: 9781536137996
Category : MATHEMATICS
Languages : en
Pages : 342

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Book Description
"Aims to present both conventional and fuzzy regression analyses from theoretical aspects followed by application examples. The present book contains chapters originating from different scientific fields. The first deals with both crisp (conventional) linear or nonlinear regression and fuzzy linear or nonlinear regression. The application example refers to the relationship between sediment transport rates on the one hand and stream discharge and rainfall intensity on the other hand. Second chapter refers to the crisp linear or nonlinear regression of six heavy metals between different soft tissues and shells of Telescopium telescopium and its habitat surface sediments. Third describes the crisp linear, multiple linear, nonlinear and Gaussian process regressions. The fourth is confronted with a classic regression model, named Geographically Weighted Regression (GWR), which constitutes a spatial statistics method. The fifth chapter regards fuzzy linear regression based on symmetric triangular fuzzy numbers. The sixth chapter treats fuzzy linear regression based on trapezoidal membership functions. The main application of this chapter concerns the dependence of rainfall records between neighboring rainfall stations for a small sample of data. The next chapter refers to the multivariable crisp and fuzzy linear regression. The eighth chapter deals with the fuzzy linear regression, with crisp input data and fuzzy output data. All the chapters offer a proper foundation of either widely used or new techniques upon regression. Among the new techniques, several innovated fuzzy regression based methodologies are developed for real problems, and useful conclusions are drawn"--

Practical Examples of Energy Optimization Models

Practical Examples of Energy Optimization Models PDF Author: Samsul Ariffin Abdul Karim
Publisher: Springer Nature
ISBN: 9811521999
Category : Technology & Engineering
Languages : en
Pages : 96

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Book Description
This book highlights state-of-the-art research on renewable energy integration technology and suitable and efficient power generation, discussing smart grids, renewable energy grid integration, prediction control models, and econometric models for predicting the global solar radiation and factors that affect solar radiation, performance evaluation of photovoltaic systems, and improved energy consumption prediction models. It discusses several methods, algorithms, environmental data-based performance analyses, and experimental results to help readers gain a detailed understanding of the pros and cons of technologies in this rapidly growing area. Accordingly, it offers a valuable resource for students and researchers working on renewable energy optimization models.

Fuzzy Linear Regression

Fuzzy Linear Regression PDF Author: Ayse Tansu
Publisher: LAP Lambert Academic Publishing
ISBN: 9783844384420
Category :
Languages : en
Pages : 220

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Book Description
In real-life situation, complexity occurs when the system is not understandable. The size, shape, position, or color of a system can cause a phenomenon. These complexities are classified in fuzzy sets. The fuzzy sets role is significant when applied to complex phenomena, which is not easily described by traditional mathematics. Fuzzy regression may be more appropriate tool than the traditional regression analysis. In fuzzy regression, it is assumed that the system's structure is ambiguous or complex.A brief review of the linear programming models in fuzzy linear regression is given. Symmetric, asymmetric, trapezoidal and bell shaped membership functions are investigated. In addition, the different linear programming models are summarized, and a new model is presented for better results. Moreover, the new model is compared with other two models that are Tanaka and Hojati models.