摘要
农业是国民经济的基础,粮食乃重中之重,粮食产量的准确预测对国家粮食安全及政府制定相应粮食生产政策具有重要的意义。该文运用灰色关联分析,从众多模糊因素中计算出云南粮食产量特有影响因子,依次为农业机械总动力、化肥施用量、农田有效灌溉面积和农村用电量,并对这些因子进行了GM(1,1)残差修正预测,把预测所得数据作为相关因素序列,以粮食产量作为系统特征序列,构建了粮食产量的灰色GM(1,N)预测模型。根据云南省1999—2015年的粮食生产相关数据,对云南省2020年的粮食产量数据进行预测,对2015年之前数据进行拟合,和实际产粮数据平均相对误差为1.92%,具有较高的精确度。通过分析预测成果,给出了确保云南省粮食产量稳固增长的对策和建议。
Agriculture is foundation of national economy,and grain is the priority among priorities. Accurate prediction of grain yield is of great significance in national food security and making grain production policy. Using grey correlation analysis method,specific factor in Yunnan grain output was analyzed from numerous fuzzy factors. The factors followed in an order as following:total power of agricultural machinery,fertilizer rate,available irrigation land area,rural electricity consumption prediction.These factors were corrected by GM( 1,1) residual correction. Predicted data was used as a sequence of related factors,and grain yield was regarded as characteristic sequence of system. A grey GM( 1,N) prediction model for grain yield was constructed. According to grain production related data in Yunnan province from 1999 to 2015,grain yield data of Yunnan province in 2020 was predicted. Fitting data until 2015,average relative error between actual output and simulation value was 1. 92%,which has high accuracy. Through analysis of prediction results,suggestions were put forward about stabilizing and improving food cereal production in Yunnan province.
出处
《农业工程》
2017年第6期157-161,共5页
AGRICULTURAL ENGINEERING
关键词
粮食产量
GM(1
N)模型
灰色预测
云南省
Grain production, Model of GM (1, N), Grey prediction, Yunnan province