Zhu-Hua Han

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Ant colony algorithm (ACA), inspired by the food-searching behavior of ants, is an evolutionary algorithm and performs well in discrete optimization. Ant colony algorithms have been recently suggested for short-term load forecasting (STLF) by a large number of researchers. In this paper, an Improved ant colony clustering (IACC) based on Ant colony algorithm(More)
Ant colony algorithm (ACA), which has been recently suggested for short-term load forecasting (STLF) by a large number of researchers, inspired by the food-searching behavior of ants, is an evolutionary algorithm and performs well in discrete optimization. In this paper, an improved ant colony clustering (IACC) based on ant colony algorithm was put forward.(More)
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(More)
Although the grey forecasting model has been successfully utilized in many fields, literatures show its performance still could be improved. For this purpose, this paper put forward a GM (1, 1)-connection improved genetic algorithm (GM (1, 1)-IGA) for short- term load forecasting (STLF). While Traditional GM (1, 1) forecasting model is not accurate and the(More)
In this paper, a GM (1, 1)-connection improved genetic algorithm (GM (1, 1)-IGA) is put forward to solve the problem of short-term load forecasting (STLF) in power system. While Traditional GM (1, 1) forecasting model is not accurate and the value of parameter OC is constant, the proposed algorithm could overcome these disadvantages. In order to construct(More)
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(More)
In this paper, an Improved Ant Colony Clustering (IACC) based on Ant Colony Algorithm is presented. In IACC, each load data was represented by an ant, and the merits of IACC were parallel search optimum and the dynamic method to adjust the evaporation coefficient, which can raise the forecast accuracy. IACC used the weighted Euclidean distance, and the(More)
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