| 张永礼，赵 蕾，董志良.基于信息粒化和PSO-SVR 模型的棉花价格波动区间和变化趋势预测[J].广东农业科学,2015,42(11):180-185 |
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基于信息粒化和PSO-SVR 模型的棉花价格波动区间和变化趋势预测 |
| Prediction of fluctuation range and change trendof cotton price based on fuzzy informationgranulation and PSO-SVR model |
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| DOI： |
| 中文关键词: 模糊信息粒化 粒子群优化算法 支持向量机 农产品价格 |
| 英文关键词: fuzzy information granulation particle swarm optimization algorithm support vector machine agricultural products prices |
| 基金项目: |
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| 摘要点击次数: 1333 |
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| 中文摘要: |
| 农产品价格的准确预测对农民规避市场风险、提高农业收入和国家农业宏观调控具有重大意义。以
国家棉花价格A 指数的预测为例，提出了一种基于模糊信息粒化和粒子群优化支持向量回归机（PSO-SVR）的农
产品价格预测时序回归模型。该模型首先使用模糊信息粒化方法，将原始国家棉花价格A 指数时间序列数据映
射为包含最小值Low、中值R、最大值Up 3 个参数的模糊信息粒，然后使用粒子群优化算法PSO 寻找支持向量
回归机（SVM）模型的最佳参数c 和g，最后，再使用优化后的支持向量回归机（SVM）模型预测国棉价格A 指数未
来波动区间和变化趋势。实证结果表明，基于模糊信息粒化和PSO-SVR 时序回归模型对国棉价格A 指数的预测
准确有效。 |
| 英文摘要: |
| Accurately predicting the prices of agricultural products is very important for evading market risk，increasing agricultural income and government macroeconomic regulation. With national cotton prices prediction asan example，this paper proposed a SVM prediction model of agricultural products prices based on fuzzy informationgranulation and particle swarm optimization algorithm. Firstly，the original national cotton prices A index time seriesdata were transformed into fuzzy information granulation particles made up of Low，R and Up. Secondly，particle swarmoptimization algorithm was used to find the best parameters c and g for SVM model. Finally，cotton price fluctuation rangeand change trend in the future were predicted by the optimized SVM regression model. The empirical analysis showedthat the PSO-SVM model was effective for the prediction of cotton price fluctuation range and change trend. |
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