Grey Data Analysis

Grey Data Analysis

AngličtinaEbook
Liu, Sifeng
Springer Nature Singapore
EAN: 9789811018411
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Podrobné informácie

This book inclusively and systematically presents the fundamental methods, models and techniques of practical application of grey data analysis, bringing together the authors' many years of theoretical exploration, real-life application, and teaching. It also reflects the majority of recent theoretical and applied advances in the theory achieved by scholars from across the world, providing readers a vivid overall picture of this new theory and its pioneering research activities. The book includes 12 chapters, covering the introduction to grey systems, a novel framework of grey system theory, grey numbers and their operations, sequence operators and grey data mining, grey incidence analysis models, grey clustering evaluation models, series of GM models, combined grey models, techniques for grey systems forecasting, grey models for decision-making, techniques for grey control, etc. It also includes a software package that allows practitioners to conveniently and practically employ the theory and methods presented in this book. All methods and models presented here were chosen for their practical applicability and have been widely employed in various research works.I still remember 1983, when I first participated in a course on Grey System Theory. The mimeographed teaching materials had a blue cover and were presented as a book. It was like finding a treasure: This fascinating book really inspired me as a young intellectual going through a period of confusion and lack of academic direction. It shone with pearls of wisdom and offered a beacon in the mist for a man trying to find his way in academic research. This book became the guiding light in my life journey, inspiring me to forge an indissoluble bond with Grey System Theory.--Sifeng Liu
EAN 9789811018411
ISBN 9811018413
Typ produktu Ebook
Vydavateľ Springer Nature Singapore
Dátum vydania 1. septembra 2016
Jazyk English
Krajina Uruguay
Autori Forrest, Jeffrey; Liu, Sifeng; Yang, Yingjie
Séria Computational Risk Management
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