Construction and Application of the Decision Tree Model for Agricultural Land Grading Based on MATLAB

Lu Zhao, Xin-qi Zheng, Hongwen Yan, Shuqing Wang, Kouqiang Zhang
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引用次数: 4

Abstract

Aiming at the insufficiencies of traditional agricultural land grading methods, this study discussed the process and technical route of agricultural land grading based on decision tree analysis method and GIS, constructed an agricultural land grading model based on MATLAB and decision tree C4.5 algorithm. Furthermore, We took Luanwan village of Pingyin county in China for the empirical study, selected seven indicators as the test attributes, predicted agricultural land grade on support of this model, and expressed the rules in the quantitative way. The results showed that agricultural land grading model based on decision tree which is coded in M-language of MATLAB doesn’t rely on the empirical knowledge. It has the ability of self-learning, and the gained rules are easy to be understood. Moreover, the high rate of accuracy will be able to meet the requirements of evaluation.
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基于MATLAB的农用地定级决策树模型的构建与应用
针对传统农用地定级方法的不足,探讨了基于决策树分析法和GIS的农用地定级流程和技术路线,构建了基于MATLAB和决策树C4.5算法的农用地定级模型。并以中国平阴县滦湾村为实证研究对象,选取7个指标作为检验属性,在此模型的支持下对农用地等级进行预测,并以定量的方式表达规律。结果表明,基于MATLAB m语言编码的决策树农用地定级模型不依赖于经验知识。它具有自学习能力,所获得的规则易于理解。而且,较高的准确率能够满足评价的要求。
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