基于关联规则与多元线性回归的云南省甘蔗产量预测模型

刘振洋; 赵家松; 胡仁傑; 刘笠溶

文章摘要

刘振洋，赵家松，胡仁傑，刘笠溶.基于关联规则与多元线性回归的云南省甘蔗产量预测模型[J].广东农业科学,2022,49(12):160-166

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Yield Prediction Model for Sugarcane in Yunnan Province Based on Association Rules and Multiple Linear Regression

DOI：10.16768/j.issn.1004-874X.2022.12.018

中文关键词: 甘蔗产量关联规则多元线性回归预测模型产量预测样本特征筛选

英文关键词: sugarcane yield association rules multiple linear regression prediction model production prediction sample feature screening

基金项目:云南省教育厅科学基金（2019J0171）；云南农业大学博士科研启动基金（A2032002507）

作者	单位
刘振洋，赵家松，胡仁傑，刘笠溶	云南农业大学大数据学院，云南昆明 650201

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中文摘要:

【目的】构建云南省甘蔗产量预测模型，对云南省甘蔗主产区甘蔗产量进行预测。【方法】选取云南省 5 个甘蔗主产区的甘蔗种植数据和地区气象数据作为研究对象，使用关联规则算法对研究区水库数、氮肥用量、磷肥用量、钾肥用量、复合肥用量、地膜使用量、甘蔗种植面积、年均气温、年降水量 9 个影响因素进行分析，得出 5 个甘蔗产量的强关联因素作为样本特征，将样本特征代入多元线性回归算法，构建产量预测模型。【结果】根据测试集验证结果显示，使用多元线性回归算法构建甘蔗产量预测模型，普洱、临沧、红河、文山、德宏地区模型的准确率分别为 81.1%、89.3%、67.8%、85.3%、73.7%；使用关联规则算法与多元线性回归算法构建甘蔗产量预测模型，普洱、临沧、红河、文山、德宏地区模型的准确率分别为 95.4%、92.8%、97.9%、94%、91.4%，关联规则算法对模型准确率的提升分别为 14.3%、3.5%、30.1%、8.7%、17.7%。【结论】关联规则算法可提升多元线性回归产量预测模型的准确率，该模型在云南省的 5 个甘蔗主产区均表现出较好的预测效果，为甘蔗产量预测提供了新的方法。

英文摘要:

【Objective】A sugarcane yield prediction model was constructed to predict sugarcane yield in the main sugarcane producing areas in Yunnan Province.【Method】The sugarcane planting data and regional meteorological data of five main sugarcane producing areas in Yunnan Province were selected as the research objects, and nine influencing factors of reservoir number, nitrogen fertilizerapplication, phosphorus fertilizer application, potassium fertilizer application, compound fertilizer application, usage of plastic film, sugarcane planting area, average annual temperature and annual precipitation were analyzed with association rule algorithm, and five strong correlation factors of sugarcane yield were obtained as sample characteristics, which were brought into multiple linear regression algorithm to construct yield prediction model.【Result】According to the test set validation results, the accuracy rates of the models using multiple linear regression algorithm to construct yield prediction models in Pu'er, Lincang, Honghe, Wenshan, and Dehong regions were 81.1%, 89.3%, 67.8%, 85.3%, and 73.7%, respectively; the accuracy rates of the models using association rule algorithm and multiple linear regression algorithm to construct yield prediction models in Pu'er, Lincang, Honghe, Wenshan, and Dehong regions were 95.4%, 92.8%, 97.9%, 94%, and 91.4%, respectively. The improved accuracy rates of models by association rule algorithm were 14.3%, 3.5%, 30.1%, 8.7%, and 17.7%, respectively.【Conclusion】The results showed that the association rule algorithm could improve the accuracy of the multiple linear regression yield prediction model, and the model showed good prediction results in all five main sugarcane producing areas in Yunnan Province, providing a new method for sugarcane yield prediction.

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