基于改进支持向量回归的农业经济评价

Min Huang
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引用次数: 1

摘要

农业工程投标本质上是一个高维非线性空间数学优化问题。为了提高SVR算法的泛化性能,采用智能算法对SVR参数进行训练,使SVR参数达到最优。将改进的支持向量回归评价模型应用于农业项目招标区域。某农业公司项目的成功实践证明了该模型的可靠性和可执行性。改进后的模型减少了人为因素的影响,提高了评价结果的客观性和公正性。
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Agricultural Economic Evaluation Based on Improved Support Vector Regression
The essence of agricultural project bid is a high-dimensional nonlinear space mathematical optimization problem. In order to improve the generalization performance of SVR algorithm, intelligent algorithm is used to train the SVR parameters, which can make the parameters of SVR optimal. The improved support vector regression evaluation model is applied to the bidding area of agricultural project. The success of some project in some agricultural company proves the reliability and enforceability of the model. The improved model reduces the influence of human factors to improve the objectivity and impartiality of evaluation results.
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