The Prediction of Greenhouse Temperature and Humidity Based on LM-RBF Network

In order to improve the accuracy of prediction for the temperature and humidity of the northern greenhouse, this paper proposes a model to predict the temperature and humidity of a greenhouse based on improved LM-RBF. The input data of the model were measured in a greenhouse in Tianjin in March. This model uses the inside and outside meteorological data of the greenhouse as input, and the temperature and humidity in a greenhouse as output. The higher prediction accuracy is obtained by the experimental results, which proved the feasibility of this scheme. This model can be used to forecast the temperature and humidity of a greenhouse and guide the control of the temperature and humidity of a greenhouse.