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Grey dynamic input–output analysis

2009; Elsevier BV; Volume: 359; Issue: 2 Linguagem: Inglês

10.1016/j.jmaa.2009.05.053

1096-0813

Qiaoxing Li,

Forecasting Techniques and Applications

A system whose information is partially known and partially unknown is named as a grey system and it is general situation in reality. On the basis of grey number/matrix and their covered operation, some definitions of grey functions are enumerated. Combining grey system theory with traditional dynamic input–output analysis, we propose the grey dynamic input–output analysis. It has two types, i.e., the continuous and the disperse. The most important results are the computational formulas of the matrix-covered set of inverse grey investment coefficient matrix. By using them, we can forecast and control the economic system under the uncertain situation. For the calculation of the matrix-covered set of inverse grey matrices, we obtain the desired formulas, which can be applied to general grey matrices. The formulas can greatly promote the development of grey theory and enrich the applied fields of uncertain mathematics. The modified case illustrates our method.