基于BP神经网络的我国蔬菜供需预测及对策研究  

Supply and Demand Forecasting Based on Back Propagation Neural Network and Countermeasure Research of China's Vegetables

作　　者：姚冠新[1,2] 徐静[1,2] 周正嵩[2] 张冬梅[1,2] 戴盼倩 

机构地区：[1]盐城工学院,江苏盐城224051 [2]江苏大学管理学院,江苏镇江212013

出　　处：《吉林师范大学学报（自然科学版）》2015年第2期4-9,共6页Journal of Jilin Normal University:Natural Science Edition

基　　金：国家自然科学基金项目(71340024;71473213);江苏省高校哲学社会科学重点项目(2014ZDIXM019);江苏省研究生创新基金项目(284);2014年度江苏省博士后科研资助项目(1401054C)

摘　　要：近年来,我国蔬菜类农产品"卖难"问题层出不穷,"微博叫卖"、"为农户找买家"现象此起彼伏,但治标不治本.对此,文章从造成农产品"卖难"问题的根源出发,通过运用BP神经网络预测模型对我国蔬菜供需量进行了预测,研究发现在蔬菜消费需求量只有微小变动的情况下,其实际供给量连续多年远高于理论供给量.为此,从合理预测供需、指导农业生产的角度提出了一些针对性的对策建议.In recent years,the“hard sell”problem of China’s vegetable produce have emerged in endlessly. The phenomenon of“Hawk”and“to find buyers for farmers”happens now and then,but it is just a temporary action instead of total solution. To this,from the root of the“hard sell”problem of agricultural products as the starting point,by using the BP neural network prediction model,the amount of supply and demand of vegetables in our country is predicted. It is found that in the situation with only minor changes in vegetable consumption demand, the actual supply is much higher than theory for many years. Therefore,some corresponding countermeasures and suggestions are put forward from the perspective of a reasonable prediction of supply and demand,as well as a scientific guidance of the agricultural production.

关 键 词：蔬菜 农产品供给 需求预测 神经网络 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程] F252.5[自动化与计算机技术—控制科学与工程]