Prediction of Dry-hot Wind Annual Pattern for Wheat Based on Markov

Based on "no aftereffect" characteristic of Markov principle, a Markov model for predicting annual pattern of wheat dry hot wind was established using meteorological data from May 13 to June 10, 2001 to 2021 in Hua County, Henan Province．Through backpropagation testing, prediction results of dry-hot wind in Hua County from 2004 to 2021 were tested, and the same data was selected for comparison with BP neural network model．Results showed that the Markov model has a prediction probability of 77.78%, it had high accuracy, and performed better than the BP neural network prediction model on the same data basis．Therefore, the Markov model could better warn against wheat dry and hot winds, and could play a role in disaster prevention and resistance, which was of great significance for improving wheat yield．