  We propose a novel approach to improve prediction accuracy of grey power
models including GM(1,1) and grey Verhulst model through optimization of the
initial condition and model parameters in this paper. And we propose a modified
grey Verhulst model. The new initial condition consists of the first item and
the last item of a sequence generated from applying the first-order
accumulative generation operator on the sequence of raw data. Weighted
coefficients of the first item and the last item in the combination as the
initial condition are derived from a method of minimizing error summation of
square. We shows that the newly modified grey power model is an extension of
the previous optimized GM(1,1) models and grey Verhulst models. The new
optimized initial condition can express the principle of new information
priority emphasized on in grey systems theory fully. The result of a numerical
example indicates that the modified grey model presented in this paper can
obtain a better prediction performance than that from the original grey model.
