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Emerald Group Publishing Limited
Article Type: Guest editorial From: Grey Systems: Theory and Application, Volume 5, Issue 2.
Perspectives on grey economic systems
Dear readers, contributors, reviewers and friends,
Grey systems research has become a referential point and an important part of the artificial intelligent techniques area, being used, over the time, in multiple applications from various fields, characterized by uncertainty and lack of information, such as: manufacturing industry, agriculture, financial sector, engineering, energy, transportation, etc.
Even though the research on the grey systems theory has begun almost 30 years ago, this field quickly turned out to be an important and fruitful area of research with strong and successful practical real-life applications.
A strong consolidation process has been made through the IEEE Grey Systems and Intelligent Services (IEEE GSIS) conferences held every two years, since 2007, which focused mainly on the development and practical applications of grey systems theory. At these conferences, a series of researchers from all over the world have met and exchanged opinions and ideas over the grey systems theory field. Nevertheless, an important contribution to the grey systems research has been made through the Emerald – Grey Systems: Theory and Application journal where high-quality papers from the grey systems theory have been published.
Due to the important contributions brought by the researchers in this field, the grey systems theory has succeeded to bridge the gap between the traditional theories and the new economic reality and has proposed a new set of methods and techniques for overcoming the changes in the environment.
In the economic field, both the macroeconomic and the microeconomic areas are characterized by uncertainty and even more, the data regarding these systems is, in most of the cases, few and hard to get. Therefore, the grey systems theory is folding on the economic areas being helpful on both their diagnosis and prediction.
For this, the present Special Issue is focusing on the advances made by the usage of grey systems theory in the economic field, stressing more on the practical applications that can be encountered here. The main purpose is to collect innovative and high-quality research contributions regarding the role played by the grey systems theory in the economic field and to explore and open new research fields for original scientific contributions in the form of both theoretical and experimental research.
Therefore, in this Special Issue of Grey Systems: Theory and Application I am pleased to introduce ten papers, each of them different in style and content, but reflecting the variety of approaches, techniques, applications and case studies in the area of economic grey systems theory and applications. Beside the strong theoretic base provided, the present issue’s papers are also presenting a significant amount of data about the way the grey systems theory can and is operating in a real-world context. As it can be seen, the great majority of the selected papers are very practical and oriented to a wide range of situations, from decision making to stock market forecasting.
The selection process was conducted in a double-blinded review manner. The reviewers’ comments indicated that the manuscripts are of high quality and relevance for the economic grey systems field.
The papers in this issue are as follows.
Liu, S.F., Zeng, B., Liu, J., Xie, N. and Yang, Y. put forward four basic models of GM (1, 1) and simulate them on homogeneous exponential sequences, nonhomogeneous exponential increasing sequences and vibration sequences, providing a foundational reference in the process of choosing the most suitable model in the economic modelling process and not only.
Zhang, J., Ran, M., Han, G. and Yao, G. propose an improvement to the classical GM (1, 1) model by employing an Aarc cot x+B function transformation in order to improve the model’s fitting effectiveness and forecasting precision. Also, a practical economical example related to the social demand of a certain commodity is put forward by the authors.
Wang, Z. and Pei, L. modify the forecasting residual of the NNGBM (1, 1) model for improving its prediction ability and extends it by using a Fourier series. The resulting model, FNNGBM (1, 1) is used on the import/export data of Chinese high-tech products, demonstrating its forecasting precision on small-sample, nonlinear time series.
Rathnayaka, R.M.K.T., Seneviratna, D.M.K.N. and Jianguo, W. examine the models that can be used for short-term economic forecasting with limited sample observations. A practical application is run on the stock market forecasting from which it can be concluded that, due to the chaotic non-stationary behavioural fluctuations, grey hybrid models are better fitting in this situations.
Scarlat, E. and Maracine, V. discuss the role of grey knowledge in the evolution of intelligent systems and present some of the architectures that can be encountered in hybrid computational intelligence models based on grey systems theory. Also, some examples of existing hybrid system architectures are provided, including evolutionary algorithms and neural networks, fuzzy logic, genetic algorithms and grey systems theory.
Zhan, H. and Liu, S.F. provide a practical economical application of grey systems theory by analysing the intermediate inputs influencing the gross products of agriculture and its composition using grey incidence analysis. The case study is made on the Huangshan city and, based on the obtained results, the authors are proposing some policy-directed advices.
Luo, D. and Li, Y. use the grey relational analysis for developing a multi-stage and multi-attribute risk group decision-making method and apply it in an economic application in which an investment bank intends to invest in three emerging companies in a city. The obtained results are underlining the effectiveness and practicability of the proposed method.
Bradea, I. and Maracine, V. examine the hospital’s performance using the grey incidence analysis. For this, using the diagnosis techniques, a series of key performance indicators are put forward in strict connection with the multiple dimensions of the performance. By using the grey systems theory, the seven key performance indicators are hierarchized, helping the hospital’s managerial team in improving its performance.
Delcea C. provides both a bibliometric analysis and a historical applications review in the last two papers of the Special Issue. For the bibliometric analysis, the Perish or Publish software was used in order to extract the papers, authors and other publishing indicators from Google Scholar database, while the ISI indexed papers were obtained by interrogating the ISI Web of Science database. In addition, a review of the most relevant publications on both grey economic diagnosis and grey economic forecasting is put forward with the aim of offering a more comprehensive picture of the contribution brought by the researchers to this particular field of grey economics.
Hoping that you will find interesting and valuable the material provided by the Special Issue, I am very grateful to the reviewers for their expert contribution in enhancing the papers, and to the authors for the quality of their work. I am glad that I could shape this Special Issue with all of you and I am confident that the grey systems theory field will continue to be an important part in the future researches. This Special Issue gives credit to all of you.
I personally thank Professor Sifeng Liu, Professor Yingjie Yang and Professor Naiming Xie for their continuous support in making this Special Issue come true.
I am also grateful to all those at Emerald for their assistance, especially to Daniel Jopling and Andrea Watson Lee.
Thank you. I hope you will enjoy this Special Issue.
Professor Delcea Camelia
Economic Informatics and Cybernetics Department, Bucharest University of Economic Studies, Bucharest, Romania