基于区间型数据计量的我国粮食产量研究

doi:10.16088/j.issn.1001-6600.2021060914

广西师范大学学报（自然科学版） ›› 2022, Vol. 40 ›› Issue (1): 206-215.doi: 10.16088/j.issn.1001-6600.2021060914

• 研究论文 • 上一篇

基于区间型数据计量的我国粮食产量研究

李城恩¹, 潘晓映¹, 王美涵¹, 施建华^1,2,3,4*

1.闽南师范大学数学与统计学院, 福建漳州 363000;
2.福建省粒计算及其应用重点实验室, 福建漳州 363000;
3.数据科学与统计重点实验室, 福建漳州 363000;
4.数字福建气象大数据研究所, 福建漳州 363000

收稿日期:2021-06-09 修回日期:2021-07-09 出版日期:2022-01-25 发布日期:2022-01-24
通讯作者: 施建华(1977—), 男, 福建福清人, 闽南师范大学教授, 博士。E-mail: v0085@126.com
基金资助:
国家社会科学基金(20XTJ003)

Research on China’s Grain Output Based on Interval Data Measurement

LI Chengen¹, PAN Xiaoying¹, WANG Meihan¹, SHI Jianhua^1,2,3,4*

1. School of Mathematics and Statistics, Minnan Normal University, Zhangzhou Fujian 363000, China;
2. Fujian Key Laboratory of Granular Computing and Applications, Zhangzhou Fujian 363000, China;
3. Fujian Key Laboratory of Data Science and Statistics, Zhangzhou Fujian 363000, China;
4. Institute of Meteorological Big Data-Digital Fujian, Zhangzhou Fujian 363000, China

Received:2021-06-09 Revised:2021-07-09 Online:2022-01-25 Published:2022-01-24

摘要/Abstract

摘要： 采用4种区间型数据计量建模方法,综合分析我国8个省份城市1993—2018年气候变化和农业生产投入要素对粮食产量影响。采用5个评价指标衡量4种建模方法的预测精度,给出4种方法的回归结果并进行比较分析,应用最优回归方法对我国粮食产量变化进行预测。研究结果表明:我国粮食产量存在地域性差异,部分省份2009以年前单位面积粮食产量变化幅度较大,但近10年我国8大产粮省份的单位面积粮食产量趋于稳定。同时,气候变化和农业生产投入要素均对我国粮食产量起显著作用。最后,本文对提高粮食产量给出相应政策建议。

关键词: 区间型数据, 面板数据, 回归分析, 粮食产量, 气候变化, 农业生产投入要素

Abstract: Four modeling methods of interval data are used to explore the comprehensive impact of climate change and agricultural production input factors on China’s grain yield from 1993 to 2018. In addition, five evaluation indexes are used to measure the prediction accuracy of methods and the regression results are given and compared. The optimal regression method is applied to predict the change of grain yield in China. The results show that there are regional differences in grain yield in China, and the grain yield per unit area in some provinces changed greatly before 2009. But the grain yield per unit area of China’s eight provinces has tended to stable in the past tent years. Furthermore, climate change and agricultural production input factors have statistical significance in China’s grain yield. Finally, some suggestions are given to improve grain yield.

Key words: interval data, panel data, regression analysis, grain yield, climate change, agricultural production input factor

中图分类号:

O212.4

李城恩, 潘晓映, 王美涵, 施建华. 基于区间型数据计量的我国粮食产量研究[J]. 广西师范大学学报（自然科学版）, 2022, 40(1): 206-215.

LI Chengen, PAN Xiaoying, WANG Meihan, SHI Jianhua. Research on China’s Grain Output Based on Interval Data Measurement[J]. Journal of Guangxi Normal University(Natural Science Edition), 2022, 40(1): 206-215.

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基于区间型数据计量的我国粮食产量研究

Research on China’s Grain Output Based on Interval Data Measurement

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