Overview
- Editors:
-
-
Cengiz Kahraman
-
Management Faculty, Industrial Engineering Department, Istanbul Technical University, Istanbul, Turkey
-
Özgür Kabak
-
Management Facult, Industrial Engineering Department, Istanbul Technical University, Istanbul, Turkey
- Provides readers with the necessary tools for making inference with fuzzy data
- Extends all the main aspects of classical statistical decision-making to its fuzzy counterpart
- Includes relevant numerical examples and case studies
- Includes supplementary material: sn.pub/extras
Access this book
Other ways to access
Table of contents (18 chapters)
-
-
- Cengiz Kahraman, Özgür Kabak
Pages 1-12
-
- I. Burak Parlak, A. Cağrı Tolga
Pages 13-34
-
- A. Cağrı Tolga, I. Burak Parlak
Pages 35-54
-
- Reinhard Viertl, Owat Sunanta
Pages 55-64
-
- Cengiz Kahraman, İrem Uçal Sarı
Pages 65-83
-
- İrem Uçal Sarı, Cengiz Kahraman, Özgür Kabak
Pages 85-99
-
- Mohsen Arefi, S. Mahmoud Taheri
Pages 101-118
-
- Reinhard Viertl, Shohreh Mirzaei Yeganeh
Pages 119-127
-
- Cengiz Kahraman, Irem Otay, Başar Öztayşi
Pages 129-154
-
- Abbas Parchami, S. Mohmoud Taheri, Bahram Sadeghpour Gildeh, Mashaallah Mashinchi
Pages 155-173
-
-
- Murat Alper Basaran, Biagio Simonetti, Luigi D’Ambra
Pages 203-220
-
-
- Cengiz Kahraman, Murat Gülbay, Eda Boltürk
Pages 263-280
-
- Nihal Erginel, Sevil Şentürk
Pages 281-295
-
- Alireza Jiryaei, Mashaallah Mashinchi
Pages 297-313
-
- R. Ivani, S. H. Sanaei Nejad, B. Ghahraman, A. R. Astaraei, H. Feizi
Pages 315-327
-
- Tzung-Pei Hong, Chun-Hao Chen, Jerry Chun-Wei Lin
Pages 329-354
-
Back Matter
Pages 355-356
About this book
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.
Reviews
“The chapters are presented in intuitive, appealing manner and logical order, making the book as accessible to the widest possible readership. … The book offers advanced methods in the field, useful practical examples and figures. The book contributes stimulating and substantial knowledge for the benefit of a host of research community and exhibits the use and practicality of the wonderful discipline statistical science. … this book will be of interest to researchers in fuzzy statistics and related fields.” (S. Ejaz Ahmed, Technometrics, Vol. 58, November, 2016)
Editors and Affiliations
-
Management Faculty, Industrial Engineering Department, Istanbul Technical University, Istanbul, Turkey
Cengiz Kahraman
-
Management Facult, Industrial Engineering Department, Istanbul Technical University, Istanbul, Turkey
Özgür Kabak
About the editors
Prof. Kahraman received his BSc (1988), MSc (1990), and PhD (1996) degrees in Industrial Engineering from the Istanbul Technical University. His main research areas include engineering economics, quality management and control, statistical decision making, and fuzzy sets applications. He has published about 150 papers in international journals and more than 5 books with Springer. He has served as guest editor of many special issues of international journals and is presently the Head of the Industrial Engineering department of the Istanbul Technical University. Dr. Özgür Kabak received his BSc (2001), MSc (2003), and PhD (2008) degrees in Industrial Engineering from the Istanbul Technical University. He is currently Assistant Professor of Industrial Engineering in the same University. His main research areas are fuzzy decision making, mathematical programming and statistical decision making.