Research on agricultural monitoring system based on convolutional neural network

被引:18
|
作者
Chen, Jinbo [2 ]
Zhou, Huiling [1 ]
Hu, Hongyu [1 ]
Song, Yan [1 ]
Gifu, Daniela [3 ]
Li, Youzhu [1 ]
Huang, Ye [2 ]
机构
[1] Huazhong Agr Univ, Coll Publ Adm, Wuhan 430070, Hubei, Peoples R China
[2] Hubei Univ Econ, Wuhan 430205, Hubei, Peoples R China
[3] Alexandru Loan Cuza Univ Iasi, Fac Comp Sci, Iasi, Romania
关键词
Social media; Agricultural monitoring system; Corpora; Convolution neural network; OIL PRICE; CAUSALITY; FLUCTUATION; FUTURES;
D O I
10.1016/j.future.2018.05.045
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
With the rapid development of social media, fluctuations in the price of vegetables are passed on to the people through the Internet in real time, which will certainly attract widespread attention in China. Therefore, Public opinion in social media is regarded as a latent factor contributing to market fluctuation. To predict the vegetable price fluctuation in China's market, a hybrid prediction model combining convolution neural network with corpora is constructed. Although a direct causality test shows the uncertainty between the vegetable price and public opinion in social media, strong causality is found after removing the seasonal effect of price. This shows that the spread of public opinion through the Internet can strengthen the link between vegetable price changes and external events by affecting the expectations of market traders. (C) 2018 Elsevier B.V. All rights reserved.
引用
收藏
页码:271 / 278
页数:8
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