摘要
随着信息技术的不断发展,各行各业对于信息技术的需求也不断提高。为提高农产品产量,通过研究农业物联网CO_(2)浓度预测,提出利用灰色预测模型的方法对农业物联网的CO_(2)浓度进行预测。利用农业物联网控制农业的生产情况,可以将数学模型与实际问题相结合,把已有数据进行建模,从而得到相对准确的CO_(2)浓度预测结果。
With the continuous development of information technology, the demand for information technology in all walks of life is also increasing. In order to improve agricultural output, this paper studies the prediction method of CO_(2) concentration in the agricultural Internet of Things and puts forward the method of using gray prediction model to predict the CO_(2) concentration in the agricultural Internet of Things. Using the agricultural Internet of Things to control agricultural production, we can combine mathematical models with practical problems, model the existing data, and obtain relatively accurate CO2concentration prediction results.
作者
高友胜
汪神羽
温凯伟
GAO You-sheng;WANG Shen-yu;WEN Kai-wei(Jiujiang Vocational University,Jiujiang,Jiangxi,China 332000)
出处
《湖南邮电职业技术学院学报》
2022年第4期18-20,共3页
Journal of Hunan Post and Telecommunication College
基金
2020年江西省教育厅科学技术研究项目“基于微服务架构的农业物联网云端数据监测系统研究”(项目编号:GJJ203910)。
关键词
CO_(2)浓度
农业物联网
灰色预测
CO_(2) concentration
agricultural Internet of Things
gray prediction
