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In literature a number of different methods are proposed to improve the prediction accuracy of grey models. However, most of them are computationally expensive, and this may prohibit their extensive use. This paper describes a much simpler scheme, based on the principle of concatenation, in which unit step predictions are concatenated by replacing the missing outputs by their previously predicted...
Under deregulated environment, accurate price forecasting provides crucial information for electricity market participants to make reasonable competing strategies. With comprehensive consideration of the influencing factors and the varying rules of the day-ahead electricity price of the PJM electricity market, a short-term electricity price forecasting method based on GM(1,2) and ARMA is proposed,...
Under deregulated environment, accurate price forecasting provides crucial information for electricity market participants to make reasonable competing strategies. With comprehensive consideration of the changing rules of the day-ahead electricity price of the United States PJM electricity market, a day-ahead electricity price forecasting method based on grey system theory and time series analysis...
This paper expounds three kinds of grey neural network combined model for short-term prediction of urban traffic speed, and confirms their validity and feasibility by conducting experiment in Beijing road of Jingzhou. Three kinds of networks are parallel grey neural network, series grey neural network, and inlaid grey neural network. The experiment proves that the three kinds of modes are feasible...
Grey Model is with the characters of less date, high precision and without prior information. In the paper, a Grey Model GM (1, 1) and a Metabolizing Model are used for the fire prediction of some province and compared them to provide decision references for the concerning governments. The case shows that Grey Model is a simple process and effective practicality. GM (1, 1) is of higher precision and...
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