Non-Equidistance GM(1,1) power and its application

GM(1,1) power model generalizes the grey Verhulst model.Based on the grey Verhulst model and the equidistance GM(1,1) power model,this paper puts forward the non-equidistance GM(1,1) power model and solves the model.In this paper,the relations of the model's curve and power's exponent, development coefficient are analyzed.At the same time the paper studies the non-equidistance GM(1, 1) power model's parameter space.The average relative error is seen as a function of power's exponent. The numeric area of power's exponent can been got according to the shape of sequences of raw data.The particle swarm optimization(PSO) algorithm is used to solve the power's exponent.Then the defects of the grey Verhulst model are overcame.Finally the example shows that the precision of the GM(1,1) power model is higher than the grey Verhulst model.So the method is feasible and effective and has important theory significance.