基于云遗传RBF神经网络的储粮温度预测研究

采用基于云理论的遗传算法对RBF神经网络算法进行优化,将优化后的算法引入到储粮温度参数分析中,对粮堆内部温度环境的变化情况进行预测。实验结果表明:优化后的算法对粮堆内温度预测具有较好的效果,预测的拟合程度很高,进而证明优化后的温度预测模型的有效性和可行性。

A GRAIN TEMPERATURE PREDICTION MODEL OF RBF NEURAL NETWORK BASED ON CLOUD GENETIC ALGORITHM

Grain is a special and complex life form , and the detection of change rules and prediction technology of temperature inside the grain bulk become extremely complicated . By combination with the characteristics of grain condition data , the genetic algorithm based on cloud theory was used to improve RBF neural net-work ,and the improved algorithm was introduced to data analysis of grain temperature to carry out the prediction of temperature environmental change inside the grain bulk . The experimental result shows that the improved algorithm to predict grain situation has good effect , and high degree of fitting .It s proved that the improved model is effective and feasible in the prediction of grain temperature .