关键词: 雷电预测, 增量学习, 时空特性, BP-ANN, 二项分类器

Abstract: In order to improve the accuracy and learning performance of the lightning prediction model, a BP-ANN binomial classifier of lightning prediction based on incremental learning and spatio-temporal characteristics is proposed. It makes a study of historical data by incremental approach and according to spatio-temporal characteristics of data, builds many BP-ANN models, classifies the new data respectively, and then uses the majority voting to determine the category of the new data. This paper constructs three kinds of lightning prediction models, BP-ANN model based on incremental learning, BP-ANN model based on spatio-temporal characteristics, and BP-ANN model combined both. The accuracy and learning performance are tested on real lightning data set, the results show the advantages and disadvantages of incremental learning, spatio-temporal characteristics and combination of both.

Key words: lightning prediction, incremental learning, spatio-temporal characteristics, BP-ANN, binomial classifier