Hongfei Niu1,2, Fanyu Meng3, Huanfang Yue3, Lihong Yang4, Jing Dong2,5, Xin Zhang2,5,*
Intelligent Automation & Soft Computing, Vol.28, No.1, pp. 93-106, 2021, DOI:10.32604/iasc.2021.010131
Abstract 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… More >