Application research on BP-ANN models of lightning prediction with spatio-temporal characteristics

To improve the accuracy and learning performance of lightning prediction models, a BP-ANN binomial classifier for lightning prediction based on incremental learning and spatiotemporal characteristics is proposed. By using incremental methods and learning historical data based on the spatiotemporal characteristics of the data, various BP-ANN models are established to predict and classify new data, and then the category of the new data is determined by majority voting. Three lightning prediction models were constructed: incremental learning-based BP-ANN model, spatiotemporal characteristic based BP-ANN model, and BP-ANN model combining incremental learning and spatiotemporal characteristic. The prediction accuracy and learning performance were tested on a real lightning dataset, and the results show the advantages and disadvantages of incremental learning, spatiotemporal characteristic, and their combination.