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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...
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 residual pheromone quantity was calculated by...
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. In IACC, each load data was represented...
Ant colony algorithms have been recently suggested for short-term electric load forecasting by a large number of researchers. As we know that the forecasting accuracy is influenced by the distributed feature of load sample space, and the complex nonlinear relation, which is formed by the sensibility of external weather factors to power load, will also reduce the accuracy of forecasting. In this paper,...
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 value of parameter a is constant, in order...
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