支持向量机
MATLAB语言
计算机科学
机器学习
土壤科学
价值(数学)
二次方程
土壤肥力
预测建模
人工智能
数据挖掘
数学
环境科学
土壤水分
几何学
操作系统
作者
Sandeep Kumar Sunori,Santosh Kumar,B. Anandapriya,S. Leena Nesamani,Sudhanshu Maurya,Manoj Kumar Singh
标识
DOI:10.1109/iceca52323.2021.9675926
摘要
The significance of pH value of soil in assessing the soil fertility has been the motivation behind writing this research paper. As the pH of the soil is strongly dependent on the extent of minerals present in it, its pH can be estimated using the mineral data. The soil data belonging to the Kumaun part of Uttarakhand is used to design the prediction models. A machine learning techniaue SVM (support vector machine) has been implemented in MATLAB version R2021a. Three different prediction models with linear, quadratic and cubic kernels are established, and their prediction accuracy is compared.
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