This paper aims to establish a novel three-way decisions-based grey incidence analysis clustering approach and exploit it to extract information and rules implied in panel data.
Because of taking on the spatiotemporal characteristics, panel data can well-describe and depict the systematic and dynamic of the decision objects. However, it is difficult for traditional panel data analysis methods to efficiently extract information and rules implied in panel data. To effectively deal with panel data clustering problem, according to the spatiotemporal characteristics of panel data, from the three dimensions of absolute amount level, increasing amount level and volatility level, the authors define the conception of the comprehensive distance between decision objects, and then construct a novel grey incidence analysis clustering approach for panel data and study its computing mechanism of threshold value by exploiting the thought and method of three-way decisions; finally, the authors take a case of the clustering problems on the regional high-tech industrialization in China to illustrate the validity and rationality of the proposed model.
The results show that the proposed model can objectively determine the threshold value of clustering and achieve the extraction of information and rules inherent in the data panel.
The novel model proposed in the paper can well-describe and resolve panel data clustering problem and efficiently extract information and rules implied in panel data.
The proposed model can deal with panel data clustering problem and realize the extraction of information and rules inherent in the data panel.
This work is partially funded by the National Natural Science Foundation of China (71503103); Humanities and Social Sciences of Education Ministry of China(17YJC640233); Soft Science Foundation of Jiangsu Province(BR2018005); Natural Science Foundation of Jiangsu Province (BK20150157); Jiangsu Province University Philosophy and Social Sciences for Key Research Program (2017ZDIXM034); Jiangsu University Natural Science Foundation Project(18KJB120010); the Fundamental Research Funds for the Central Universities (2017JDZD06). Even so, this work does not involve any conflict of interest.
Liu, Y., Du, J., Zhang, R. and Forrest, J. (2019), "Three way decisions based grey incidence analysis clustering approach for panel data and its application", Kybernetes, Vol. 48 No. 9, pp. 2117-2137. https://doi.org/10.1108/K-08-2018-0445Download as .RIS
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