中国水利水电科学研究院学报Issue(2)：162-169,8.DOI:10.13244/j.cnki.jiwhr.2014.02.008
基于支持向量机的微咸水灌溉下土壤盐分预测
Application of support vector machine method to prediction of soil salinity
摘要
Abstract
The soil water and salt migration process is one of the most important foundations for water salt regulation in farmland. It is also an extremely complicated physical and chemical process. Based on the ex-periments on saline and fresh water alternate irrigation in laboratory, this study introduced the model of supporting vector machine (SVM) was introduced in to predict soil electrical conductivity (EC) and pH af-ter saline and fresh water alternate irrigation. The results show that support vector machine (SVM) models can predict soil EC and pH values effectively under saline and fresh water alternate irrigation, the average relative error is less than 10%, and the higher forecasting accuracy can be acquired by using SVM model. Therefore,the SVM model is a very useful tool for soil water and salt migration study.关键词
微咸水灌溉/土壤盐分/支持向量机/预测Key words
saline water irrigation/soil salinity/support vector machines/prediction分类
农业科学引用本文复制引用
吕烨,阮本清,管孝艳,王少丽..基于支持向量机的微咸水灌溉下土壤盐分预测[J].中国水利水电科学研究院学报,2014,(2):162-169,8.基金项目
国家自然科学基金项目（51109227，51009152，51079162）；水利部948项目 （）
