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Foreword (1) to Grey Systems Analysis: Methods, Models and Applications
2nd Edition
E. K. Zavadskas
The Journal of Grey System
2024, 36 (5):
106-106.
As a new edition of Grey Systems Analysis by Professor
Sifeng Liu is about to be published, I am great honored to write the
preface for this classic work in the field of grey systems research.
In the mid to late 20th century, human society began to move
towards the information age.People are beginning to deeply realize
that data analysis methods have become an indispensable skill for
everyone.The characteristics and operating rules of various
systems are like gold buried in a sea of sand, deeply concealed by
the chaotic and complex data information, and there is an urgent
need for effective scientific methods to explore and reveal.In
response to the needs of the times, as a poverty information data
analysis method, grey system theory has emerged. Grey system
theory takes the "poor data" uncertain system with "some
information known and some information unknown" as the
research object. It mainly extracts valuable information through the
mining of "some" known information, and realizes the correct
description of the system operation behavior and evolution law, so
that people can use mathematical models to analyze and assess the
"poor data" uncertain system, then realize high-precision
prediction, scientific decision-making and optimal control of the
"poor data" uncertain system.
Prof. Liu has been dedicated to grey system research for 40
years, and his series of original concepts and models have become
classics in the field. Such as general grey numbers, simplified
forms of grey numbers, and their algebraic systems; Construction
and properties of sequence operators and practical buffer operators;
A series of grey relational analysis models based on a global
perspective; The grey evaluation model based on a mixed
possibility function of endpoints and center points, a multiobjective
weighted intelligent grey target decision-making model,
and a two-stage grey decision-making model based on a kernel
weight vector group; And various original poverty information data
prediction models such as original difference models, mean
difference models, discrete grey models, fractional order grey
models, and self memory models proposed in collaboration with
his students.
Especially his seminal books, greatly promoted the
dissemination and development of grey system theory. The Grey
System Theory and Its Applications, first published in 1991, were
deeply loved by readers. In 2024, Science Press released its 10th
edition, which was rated as the first highly cited book in pandect of
Natural Science by China National Knowledge Infrastructure.
Multiple English versions, such as An Introduction to Grey System
Theory(1998, IIGSS Academic Publisher, USA), Grey
Information(2006, Springer London Ltd, UK), Grey Systems (2011,
Springer-Verlag, DE), Grey Data Analysis (2016, Springer, SG),
Grey Systems Analysis (2022, Springer, SG), are the first choice
for scholars from all over the world to understand grey system
theory and its research progress.
Currently, scholars from over 130 countries or regions around
the world have published papers on grey systems. My team has
been conducting grey system theory research for over 20 years.
And starting to publish papers related to grey systems in the early
21st century.We have successfully applied grey system methods
and models to solve problems such as construction project
evaluation and supplier selection, and proposed multiple combined
grey models, such as COPRAS-G, ARAS-G, and EDAS-G, etc.
This book will undoubtedly benefit more grey system theory
learners and researchers as it is published in OA format with the
support of the Excellent Academic Works Publishing Fund of
Northwestern Polytechnical University. Grey system theory is a
powerful tool for analyzing uncertain data in the era of big data. I
look forward to its widespread dissemination worldwide,
promoting the in-depth application of grey system theory in the
fields of natural sciences, social sciences, and engineering
technology.
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