Prediction Model of Wind Speed and Direction Using CNN and CLSTM with Vector Image Input

抄録

We describe a wind speed prediction method using wind vector images as input. The prediction model combines convolutional neural network (CNN) and convolutional long short-term memory (CLSTM), which are effective for image analysis. Several input image data structures expressing wind vector change are considered and the prediction accuracy is compared between them. The performance of the proposed method is evaluated by the root-mean-square error and correlation coefficient between observed and predicted values.