摘要
准确预测农产品市场价格对政府宏观调控和农业生产者制定生产决策具有重要意义。本研究提出了一种基于模糊信息粒化和遗传算法的支持向量机(GA-SVM)农产品价格预测模型。该模型首先将原始价格数据进行模糊信息粒化,然后利用支持向量机对粒化后的价格数据做出预测。为提高预测精度,利用遗传算法对支持向量机的参数进行优化。对国内某农产品批发市场的价格数据进行实证分析的结果表明,该方法能对农产品价格的变化范围进行有效地预测。
Accurately predicting the prices of agricultural products is very important for government macroeconomic regulation and agricultural producers＇ production decisions.In this paper,a SVM prediction model of agricultural products prices which was based on fuzzy information granulation and genetic algorithm was presented.This model firstly granulated the original price data,next used genetic algorithm to optimize the support vector machine＇s parameters,and then made a prediction for the granulated price data.With the price data of one domestic agricultural products wholesale market,the empirical analysis showed that this method could predict the variation range of prices of agricultural products effectively.
出处
《农业网络信息》
2012年第11期16-20,共5页
Agriculture Network Information
关键词
模糊信息粒化
遗传算法
支持向量机
农产品价格
fuzzy information granulation
genetic algorithm
support vector machine
agricultural products prices
