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基于ε-SVR的粮食产量预测模型及应用 被引量:9

Modeling and prediction of foodstuff output based on ε-SVR method.
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摘要 提出一种基于支持向量回归的粮食产量预测方法,以浙江省近14年的粮食产量统计数据作为分析对象,选择影响粮食产量的农业从业人员、谷物播种面积、粮食总种植面积、农村机械总动力、农村用电量、受灾面积、成灾面积、上一年粮食收购价格、有效灌溉面积和化肥施用量等10个因素,用1991—2002年的产量数据进行建模,得到98.47%的拟合精度.应用这一模型,对2003和2004年度的粮食产量进行预测,分别达到97.5%和95.8%的预测精度.说明该方法适合用于粮食产量分析和短期预测,为粮食产量预测提供了一种新方法. A new foodstuff output prediction method was investigated based on e-support vector regression (ε-SVR). The statistical data of foodstuff output of Zhejiang Province in the last 14 years were applied as the analytical matrix. The influence factors of foodstuff output were the following 10 aspects, including agricultural practitioners, cereal sown area, total foodstuff plant area, total power of farm machinery, electricity consumed in rural area, area of affected crops, disaster-affected areas, foodstuff purchasing price of preceding year, effective irrigated area and fertilizing amount. The foodstuff output data of year 1991--2002 were applied as calibration set to develop ε-SVR model, and the prediction precision was 98.47 %. The foodstuff output of year 2003 and 2004 was used as validation set, and the prediction precision by the above developed ε-SVR model were 97.5% and 95.8% for year 2003 and 2004, respectively. The results above indicate that ε-SVR is suitable for the analysis and short-term prediction of foodstuff output, and ε-SVR supplies a new method for the prediction of foodstuff output.
出处 《浙江大学学报(农业与生命科学版)》 CAS CSCD 北大核心 2009年第4期439-443,共5页 Journal of Zhejiang University:Agriculture and Life Sciences
基金 国家自然科学基金资助项目(30671213) 教育部青年教师教学科研基金资助项目
关键词 ε-SVR 粮食产量 短期预测 ε-SVR foodstuff output short-term prediction
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