基于支持向量机的标准农田地力等级评价——以浙江省温州市鹿城区为例
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Productivity evaluation and grading of standard cultiveated land based on Support Vector Machine——a case study of Lucheng district of Wenzhou city, Zhejiang Province
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    摘要:

    提出了一种基于支持向量机(SVM)的标准农田地力等级评价方法,并给出了遗传算法-模拟退火(GASA)优化SVM参数算法。该方法首先在确定标准农田地力等级评价指标的基础上,利用地力调查样本数据及传统的指数和法评价结果构造SVM样本集,然后运用GASA优化SVM参数算法训练SVM,建立标准农田地力等级的SVM评价模型。应用该方法对温州市鹿城区标准农田地力等级进行了评价,结果为:2级田和3级田分别占测试样本代表标准农田总面积(115.7 hm2)的45.04%和54.96%,该方法的评价正确率为100%。应用BP神经网络法对测试样本进行评价,其评价正确率为90%。结果表明,SVM 用于标准农田地力等级评价,具有比BP神经网络更高的评价精度,可有效用于标准农田地力等级评价,为耕地地力评价提供了新方法。

    Abstract:

    A SVM (Support Vector Machine)-based method for productivity evaluation of Standard Cultivated Land (SCL) and a GASA-optimized algorithm for selecting of SVM parameters is put forward in this paper. Based on determination of the indices for productivity evaluation and grading of SCL, this method first made use of the data of the samples in the farmland productivity survey and its evaluation results of traditional integrated productivity factors method in building up a SVM sample set, trained SVM with the GASA-optimized algorithm, and set up a SVM model for evaluation and grading of SCL. This method was tested on productivity evaluation of SCL in Lucheng District of Wenzhou City, Zhejiang. The results indicate that the second grade and third grade of SCL accounts for 45.04% and 54.96%, respectively, of the total SCL in area ( 115.7 hm2 ) which the test samples stand for. The evaluation using this method reached 100% in accuracy. The evaluation of the test samples using the BP networks method was only 90% in accuracy. The findings show that the SVM method is much higher in accuracy than the BP networks method, and therefore this effective new method can be used efficiently to evaluate and grade SCL in productivity.

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赖红松,吴次芳.基于支持向量机的标准农田地力等级评价——以浙江省温州市鹿城区为例[J].土壤学报,2012,49(5):850-861. DOI:10.11766/trxb201105170176 Lai Hongsong, Wu Chifang. Productivity evaluation and grading of standard cultiveated land based on Support Vector Machine——a case study of Lucheng district of Wenzhou city, Zhejiang Province[J]. Acta Pedologica Sinica,2012,49(5):850-861.

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  • 收稿日期:2011-05-17
  • 最后修改日期:2012-03-12
  • 录用日期:2012-04-01
  • 在线发布日期: 2012-07-02
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