To solve the problem that non periodicity and randomness of data in predicting the near wind speed of high-speed trains,a near wind speed prediction and warning system based on BIRCH clustering and LSTM algorithm is constructed.The system firstly performs cross validation of historical data,then uses BIRCH for online incremental clustering.Finally,based on the clustering results,the data closest to the current predicted time series is selected for LSTM rolling training and predicted to obtain the prediction and warning results.Therefore,the method has characteristics of not relying on numerical prediction products and adapting to random data.Experiments show that two algorithms of system are run in parallel,with high efficiency and good prediction results.Thus,it is a new way to solve the problem of strong wind speed pre-diction.
关键词
高速铁路/风速/预测预警/聚类/递归神经网络
Key words
high speed railway/wind speed/prediction and warning/clustering/recurrent neural network
维普
万方数据