Neural network wind speed prediction method based on time series data analysis

The invention discloses a neural network wind speed prediction method based on time sequence data analysis. The method comprises the steps of obtaining multiple groups of time sequence data of a windpower plant; respectively establishing regression models of the meteorological data, and recording meteorological attribute values after regression; establishing a BP neural network model, performinggrouping training on the neural network model by adopting a difference operation and firefly mixed algorithm, and performing global training; calculating a latest meteorological attribute value afterregression through the latest historical meteorological data; and inputting the latest meteorological attribute value into a neural network, and calculating a predicted wind speed value. According tothe method, regression trend data is adopted to replace fixed data of a certain day period to train the model, a BP neural network is improved by utilizing a difference algorithm and a firefly algorithm, and a method of combining grouping training and global training is adopted, so that the prediction accuracy of the method is higher than that of a traditional method.