Grey Unbiased GRM(1,1) Model Based on Accumulated Generating Operation in Reciprocal Number and its Application
The accuracy of the grey model is not high for the monotonic decreasing data and the error can not avoided. The model can not satisfy the compatibility conditions and then it is not accordant with the linear transformation. The paper adopts the equal interval unbiased model and takes one of the components in as the initial values. By this method it induces the parameters in the grey unbiased GRM(1,1) model and establishes the equal interval unbiased model based on the reciprocal AGO process. The model has high accuracy and has good value in the theory and practice. The examples show it is practical and reliable.
Helen Zhang and David Jin
D. G. Liao and Y. X. Luo, "Grey Unbiased GRM(1,1) Model Based on Accumulated Generating Operation in Reciprocal Number and its Application", Advanced Materials Research, Vol. 321, pp. 29-32, 2011