Greenhouse Temperature Forecast Based on Improved PSO for Optimizing RBF Neural Network
WANG Yuanyuan
Abstract：Based on the meteorological data and outside greenhouse as input,the greenhouse temperature humidity and other meteorological factors as the output,the prediction model of greenhouse environment temperature and humidity with improved RBF neural network based on improved PSO algorithm.The simulation test and performance evaluation are carried out to verify the feasibility and effectiveness of the proposed method through the experiment.The model is convenient for da-ta acquisition,few parameters and high accuracy,which provides scientific basis for the prediction,regulation and manage-ment of extreme temperature in greenhouse.
Keywords：RBF neural networkPSO algorithmprediction modelgreenhouse
Publication Date：2016-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：6( 1210-1215 )