基于灰色变权组合模型的河南粮食产量预测分析
Forecasting analysis of grain yield in Henan Province based on grey variable weight combination model
张雅玉 1李佳欣 1王丰效1
作者信息
- 1. 喀什大学数学与统计学院,新疆喀什 844000
- 折叠
摘要
科学合理地考虑各生产资源要素在农业中的运用,促进粮食产量的稳定增长,是保障粮食安全的关键.选取河南省 2005～2021 年粮食产量及相关因素数据,利用灰色关联模型提取影响粮食产量的主要影响因素,基于方差倒数加权法构建由GM(1,N)、Lasso回归、BP神经网络组成的多变量变权重组合预测模型,对河南粮食产量的变化趋势进行拟合与预测.结果表明,变权重组合预测模型的预测误差为 0.589%,预测精度高且性能稳定;预测河南粮食产量在 2022～2025 年将会保持稳定增长,并在 2025 年达到 73 282.65 kt.
Abstract
It is the key to ensure food security to scientifically and reasonably consider the application of various production resource elements in agriculture and promote the steady growth of grain output.The data of grain production and related factors in Henan Province from 2005～2021 were selected.And grey correlation model was used to extract the main influencing factors of grain production.Based on the inverse variance weighting method,a multivariate quantitative weight combination prediction model consisting of GM(1,N),Lasso regression and BP neural network was constructed.The change trend of grain output in Henan Province was fitted and predicted.The results showed that the prediction error of the variable weight combination prediction model was 0.589%,which had high prediction accuracy and stable performance.It was predicted that grain production in Henan would maintain a steady growth in 2022～2025 and reach 73 282.65 kt in 2025.
关键词
粮食产量/灰色关联分析/方差倒数加权法/变权组合预测Key words
grain output/grey correlation analysis/inverse variance weighting method/variable weight combination prediction引用本文复制引用
出版年
2024
国家科技期刊平台
NSTL
万方数据