A Wind Speed Prediction Model Based on ARIMA and Improved Kalman Filter Algorithm

Abstract

This article is dedicated to solving the problem of wind speed prediction. A time series analysis method based on the establishment of a differential autoregressive sliding model for simple training and a prediction model to obtain the state is proposed. The Kalman filter method with adaptive weighting coefficients is used to predict the equation, and the experimental results show that the composite algorithm can effectively reduce the prediction error.