@Article{iasc.2021.010131, AUTHOR = {Hongfei Niu, Fanyu Meng, Huanfang Yue, Lihong Yang, Jing Dong, Xin Zhang}, TITLE = {Soil Moisture Prediction in Peri-urban Beijing, China: Gene Expression Programming Algorithm}, JOURNAL = {Intelligent Automation \& Soft Computing}, VOLUME = {28}, YEAR = {2021}, NUMBER = {1}, PAGES = {93--106}, URL = {http://www.techscience.com/iasc/v28n1/41757}, ISSN = {2326-005X}, 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 errors in three different farms were below 2.32.}, DOI = {10.32604/iasc.2021.010131} }