TY  - JOUR
AB  - Purpose The purpose of this paper is to overcome the shortcomings of existing multivariate grey incidence models that cannot analyze the similarity of behavior matrixes.Design/methodology/approach First, the feasibility of using gradient to measure the similarity of continuous functions is analyzed theoretically and intuitively. Then, a grey incidence degree is constructed for multivariable continuous functions. The model employs the gradient to measure the local similarity, as incidence coefficient function, of two functions, and combines local similarity into global similarity, as grey incidence degree by double integral. Third, the gradient incidence degree model for behavior matrix is proposed by discretizing the continuous models. Furthermore, the properties and satisfaction of grey incidence atom of the proposed model are research, respectively. Finally, a financial case is studied to examine the validity of the model.Findings The proposed model satisfies properties of invariance under mean value transformation, multiple transformation and linear transformation, which proves it is a model constructed from similarity perspective. Meanwhile, the case study shows that proposed model performs effectively.Practical implications The method proposed in the paper could be used in financial multivariable time series clustering, personalized recommendation in e-commerce, etc., when the behavior matrixes need to be analyzed from trend similarity perspective.Originality/value It will promote the accuracy of multivariate grey incidence model.
VL  - 7
IS  - 2
SN  - 2043-9377
DO  - 10.1108/GS-04-2017-0007
UR  - https://doi.org/10.1108/GS-04-2017-0007
AU  - Zhang Ke
AU  - Zhong Qiupin
AU  - Zuo Yuan
PY  - 2017
Y1  - 2017/01/01
TI  - Multivariate grey gradient incidence model and its application
T2  - Grey Systems: Theory and Application
PB  - Emerald Publishing Limited
SP  - 236
EP  - 246
Y2  - 2024/04/26
ER  -