Prediction of Grain Humidity Based on Improved Grey Markov Model

摘要

In view of the application background of grain storage technology, food security has become a top priority. It is the key to solving the problem of food security reserve. These parameters can affect the grain storage status, such as temperature and humidity. The choice of forecasting method is the key to determining the final forecast level. The traditional Grey Model is more suitable for short-term prediction. Based on this shortcoming, the article combines Markov theory and the idea of grey prediction to establish the Grey-Markov prediction model, which is compared with the traditional grey model (referred to as GM(1,1)). the feasibility of the grey Markov prediction model is obtained in the paper. What’s more, a new dimension improved Grey-Markov model is proposed. The experiment verifies that the new dimension improved Markov prediction model is more suitable for long-term prediction, and the prediction results are accurated, which can provide valuable reference data for food security reserves.