Abstract
Rough Set Theory (RST) is a powerful mathematics tool, which can deal with fuzzy and uncertain knowledge, and radial basis function (RBF) neural network has the ability to approach any nonlinear function precisely. According to the non-linear relation characteristics of ship power load, a short-term load prediction method based on RST and RBF neural network is presented in this paper. Using RST on the advantage of data analysis, the important input nodes can be selected, followed by a second stage selecting the important centers and leaning the weights of hidden nodes. The experimental results proved that this method could achieve greater predictive accuracy and generalization ability.
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