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A New New-Information Optimized MGRM (1, n) Model Based on the Reciprocal Accumulated Generating Operation

Lijun YANG, Zhiheng DENG, Xueliang JIANG


Grey system theory is a scientific theory to study poor information a wide range of adaptability. This paper constructed the new-information background values of the multivariable non-equidistant new-information grey model MGRM(1, n) using the modeling method of progressive optimization. The m’th component of the data was taken as the starting value of the solution of grey differential equations, the condition of the target function was set as having the minimum relative error, and the correction of the original value was taken as the design variable. And the multivariable non-equidistant grey new-information model MGRM(1, n) was built based on the reciprocal accumulated generating operation. This model, with high precision and easy access, is suitable for both equidistant and non-equidistant modeling, and it extends the applied range of the grey model. And the practicality and the reliability of the model built were proven by real cases.


non-equidistant sequence, progressive optimization modelling, new-information, optimization, MGRM (1, n) model, least square method.

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