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基于改进的SVM算法的耕地地力评价模型研究
引用本文:李露璐. 基于改进的SVM算法的耕地地力评价模型研究[J]. 沈阳农业大学学报, 2012, 43(1): 126-128
作者姓名:李露璐
作者单位:玉林师范学院计算机科学与工程学院,广西玉林,537000
基金项目:广西省自然科学基金项目
摘    要:为了提高农业管理水平,将计算机智能技术与农业技术相结合,提出基于改进的SVM算法建立标准农田地力等级的评价模型,在评价模型中利用频繁闭集挖掘算法获取特征向量集合,再利用SVM算法建立耕地地力评价模型。仿真结果表明:评价结果符合当地实际情况,并且与传统的评价模型相比,该模型对非线性特征值评价评价中精确度更高。

关 键 词:耕地地力  支持向量机  评价模型

Model of Productivity of Cultivated Land Based on Improved-SVM
LI Lu-lu. Model of Productivity of Cultivated Land Based on Improved-SVM[J]. Journal of Shenyang Aricultural University, 2012, 43(1): 126-128
Authors:LI Lu-lu
Affiliation:LI Lu-lu (College of Computer Science and Engineering,Yulin Normal College,Yulin Guangxi 537000,China)
Abstract:In order to improve the level of management of agriculture and combined with artificial intelligence,a standard evaluation on soil fertility grade for cultivated land was made based on improved-SVM.This model used data mining algorithm of FCIs to obtain the list of feature vectors,then the evaluation model of soil fertility grade for cultivated land was established by SVM algorithm.The experiment result was basically consistent with the actual status,status,showed that the model is better practiocable and higher accuracy for evaluation of the nonlinear characters.
Keywords:productivity of cultivated land  support vector machine  evaluation model
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