Forecasting Grain Supply and Demand with Support Vector Regression

Autor: Dong-li Liu, Tie-jun Yang, Wei-ya Shi
Rok vydání: 2017
Předmět:
Zdroj: DEStech Transactions on Computer Science and Engineering.
ISSN: 2475-8841
DOI: 10.12783/dtcse/cece2017/14507
Popis: The paper uses the machine leaning algorithm to analyses grain supply and demand of China. For the sake of small samples, support vector regression is used to forecast the tread of grain supply and demand. From the result, it can be found that support vector regression can get good performance using some different metrics. The result also shows that both grain supply and demand will increase in long tread. At last, some suggestions about grain supply and demand are given.
Databáze: OpenAIRE