Emerging studies and applications of grey systems




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Peer reviewed



At a time when most researchers and businesses are talking about Big Data, small and incomplete data are never far away from us. In fact, most of our decisions are made under incomplete and small data. There are many areas where small and incomplete data are inevitable, such as health care, traffic management, economic analysis, etc. The theory of grey systems emerged as a novel solution to deal with small and incomplete data, and it is attracting more and more attention from researchers and professionals in different disciplines. It has the ability to establish models from extremely limited data under uncertainty, which is usually difficult for other models.

Although grey systems provide powerful capability in data analysis, its impacts in applications have mainly materialized in China. I have frequently received questions regarding the differences between Grey systems and other related models, and to provide examples of their real world use. To promote grey systems and its applications, an international research network was formed under the support of the Leverhulme Trust in 2015. The leading experts from UK, China, Canada, Romania and Spain formed the core of the network. A number of activities were conducted to foster the collaboration between members of the network. As a result, the international association of grey systems and uncertainty analysis was established in 2016. Through our discussion in the network and the association, it was deemed necessary to assemble the latest advance in this field to clarify confusions between grey systems and grey sets with other models, and provide a collection of successful application cases as guidance for people interested in applying grey systems to their problems. Therefore, a collection of contributions from our network partners and leading experts in the field is put together to form this book. The contributors include world leading experts as well as a new generation of research leaders from both Europe and China. The application covers many different disciplines, ranging from social economics to engineering, energy and management.

The book focuses mainly on two themes: 1. The connection between grey systems and other related models, such as fuzzy sets and rough sets (chapter 3-5). 2. Successful real world applications in different disciplines (chapter 6-12). To introduce to the readers who have no background in grey systems, a brief introduction is also included (chapter 1-2).

Chapter 1 is a general overview of the whole field of grey systems and its recent development. It helps the readers to see the development and the state of the art of this field. Chapter 2 then gives a brief introduction to the fundamental concepts in grey systems, especially grey models so as to enable the readers to understand other chapters. These two chapters lay the essential backgrounds for the contents in other chapters. Chapter 3 then moves into the connection between grey systems, especially grey sets with various fuzzy sets and rough sets. It helps to clarify the confusions between grey systems and fuzzy sets and rough sets. Chapter 4 focuses on the hybridization of grey systems with neural-fuzzy systems and illustrates how they can be integrated together. Chapter 5 puts grey systems into a more general level and puts forward the novel concept of grey knowledge. These three chapters demonstrate the distinctive and collaborative features of grey systems in uncertainty modelling. Starting from Chapter 6, the remaining chapters cover various real world application studies. Chapter 6 reveals how to apply grey systems in economic studies using agent-based systems. Chapter 7 demonstrates how grey systems help with the short term forecasting of traffic flow. Chapter 8 illustrates how grey models are applied to predict and manage Yellow River ice disasters in China. Chapter 9 showcases the application of grey systems to social network data analysis. Chapter 10 gives some case studies in applying grey systems into the energy-economic system. Chapter 11 explains how to select business strategy using grey stratified decisions model. Finally, Chapter 12 illustrates a cost level analysis for the components of the smartphones using greyness based quality function deployment. The cases studies in Chapter 6-12 covers a wider range of disciplines, geographical areas and different culture backgrounds, and it can serve as a useful reference for practitioners challenged by small and incomplete data. Combined with the connections covered in Chapter 3-5 and the basics in Chapter 1-2, this book will provide a convenient handbook for the practical application of grey systems.



Grey systems, Uncertainty Modelling, Grey numbers, Grey sets, Grey models


Yang, Y. and Liu, S. (2023) Emerging studies and applications of grey systems, editors, Springer, pp.330. .


Research Institute

Institute of Artificial Intelligence (IAI)