Soil Moisture Prediction in Peri-urban Beijing, China: Gene Expression Programming Algorithm
文献类型： 外文期刊
作者： Niu, Hongfei 1 ; Meng, Fanyu 3 ; Yue, Huanfang 3 ; Yang, Lihong 4 ; Dong, Jing 2 ; Zhang, Xin 2 ;
作者机构： 1.Liaoning Vocat Coll Ecol Engn, Shenyang 110122, Peoples R China
2.Beijing Acad Agr & Forestry Sci, Natl Engn Res Ctr Informat Technol Agr, Beijing 100097, Peoples R China
3.Beijing Agr Technol Extens Stn, Beijing 100029, Peoples R China
4.Yunnan Agr Vocat & Tech Coll, Kunming 650031, Yunnan, Peoples R China
5.Minist Agr, Key Lab Qual Testing Hardware & Software Prod Agr, Beijing 100097, Peoples R China
关键词： GEP; prediction; soil moisture
期刊名称：INTELLIGENT AUTOMATION AND SOFT COMPUTING （ 影响因子：1.276； 五年影响因子：1.177 ）
ISSN： 1079-8587
年卷期： 2021 年 28 卷 1 期
页码：
收录情况： SCI
摘要： Soil moisture is an important indicator for agricultural planting and agricultural water management. People have been trying to guide crop cultivation, formulate irrigation systems, and develop intelligent agriculture by knowing exactly what the soil moisture is in real time. This paper considers the impact of meteorological parameters on soil-moisture change and proposes a soil-moisture prediction method based on the Gene Expression Programming (GEP) algorithm. The prediction model is tested on datasets from Shunyi, Yanqing and Daxing agricultural farms, Beijing. The results show that the GEP model can predict soil moisture with a maximum correlation coefficient of 0.98, and the root-mean-square errors in three different farms were below 2.32.
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