论文部分内容阅读
建立粮仓温湿度的预测模型,对实现粮食的安全储备有着积极意义。但粮仓温湿度数据的贫乏性和其随季节变化的波动性,一直是困扰粮仓温湿度建模的难题,这也使粮仓的温湿度控制一直处于被动局面。利用灰模型贫数据建模的特点,提出了采用改进的GM(2,1)模型对粮仓检测到的温湿度数据进行建模分析的方法,得到粮仓的温湿度预测模型,实现对粮仓温湿度变化趋势的预测和预警。仿真结果表明,该模型的预测值有较高的精度,因此,有一定的实用价值。
The establishment of a forecast model of temperature and humidity in granary has a positive meaning to realize the safe storage of grain. However, the lack of data on the temperature and humidity of the granary and its fluctuation with the seasons have always been a problem that plagued the granary temperature and humidity modeling, which has also kept the temperature and humidity control of the granary in a passive situation. Based on the characteristics of gray model and poor data modeling, this paper proposed a method of modeling and analyzing the temperature and humidity data detected by granary using improved GM (2,1) model, obtained temperature and humidity forecasting model of grain silo, Prediction and warning of changing trends. The simulation results show that the prediction value of the model has higher accuracy, therefore, it has some practical value.