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GM model is widely applied in many fields, in this paper, a refined GM(l,l)-improved genetic algorithm (GM(1,1)- IGA) is put forward to solve short-term load forecasting (STLF) problems in power system. Traditional GM(1,1) forecasting model is not accurate and the value of parameter a is constant, while the proposed algorithm could overcome these disadvantages. GM(1,1)-IGA established a function Z(c)...
According to Traditional Grey Model (GM(1, 1)) is not accurate and the value of parameter is constant, in order to overcome these disadvantages, this paper put forward an improved genetic algorithm-GM(1, 1) (IGA-GM (1, 1)) to solve the problem of short-term load forecasting (STLF) in power system. The proposed algorithm not only improved the original series but also constructed optimal grey model...
A mathematical model known as grey model GM(1,1) has been employed successfully in the forecasting of power load system. Because traditional GM (1, 1) forecasting model is not accurate and the value of parameter alpha is constant, so this paper put forward a improved genetic algorithm - GM (1, 1) (IGA-GM (1, 1)), the proposed algorithm were used to solve the problem of short-term load forecasting...
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