摘要
利用机器学习技术,基于历史销量数据和钢材产量、橡胶轮胎产量、货币供应量、百度搜索指数、居民消费价格指数等,建立多因素非线性自回归汽车销量预测模型。
Based on the historical sales data, steel production, rubber tire production, money supply, Baidu searching index, consumer price index, etc., a multi- factor nonlinear autoregressive automobile sales forecasting model was established by using machine learning technology.
作者
王书鹏
迮恒鹏
王涛
黄素珍
刘桂兰
Wang Shupeng;Ze Hengpeng;Wang Tao;Huang Suzhen;Liu Guilan(School of Economics and Management, Yancheng Institute of Technology, Yancheng, Jiangsu, 224051;School of Electrical Engineering, Yancheng Institute of Technology, Yancheng, Jiangsu, 224051;School of Mathematical, Yancheng Institute of Technology, Yancheng, Jiangsu, 224051)
出处
《中阿科技论坛（中英阿文）》
2019年第2期26-27,31,10034-10036,共6页
China-Arab States Science and Technology Forum
关键词
机器学习
非线性自回归
时间序列
销量预测模型
machine learning
nonlinear auto regression
time series
sales forecasting model
