Soil Moisture Prediction in Peri-urban Beijing, China: Gene Expression Programming Algorithm

被引：2
|
作者：
Niu, Hongfei [1 ,2 ]
Meng, Fanyu [3 ]
Yue, Huanfang [3 ]
Yang, Lihong [4 ]
Dong, Jing [2 ,5 ]
Zhang, Xin [2 ,5 ]
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
来源：
INTELLIGENT AUTOMATION AND SOFT COMPUTING | 2021年 / 28卷 / 01期
基金：
国家重点研发计划;
关键词：
GEP; prediction; soil moisture;
D O I：
10.32604/iasc.2021.010131
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
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.
引用
收藏
页码：93 / 106
页数：14
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