Abstract
In this paper, a new ant colony algorithm is introduced and a new feedforward network training strategy, ACOBP algorithm, is proposed for the first time, based on the traditional linear feedforward neural network and BP algorithm. In this paper, the network is used for load forecasting and the results of the example show that this method is feasible and reasonable. In the aspect of sample data processing, this paper has fully considered the influence of several main factors on the load variation, and quantified a series of weather factors, such as temperature and rainfall, and forecasted the important holiday separately. By analyzing the special law of load, the network parameters are adjusted and the precision of prediction is improved.
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