2021年4月29日上午9：00437必赢会员中心网页版统计学博士生徐定鑫为我院师生做学术报告，报告地点为南湖校区教学科研楼205室，我院部分老师及全体研究生参与了本次学术报告会。
报告题目：A deep learning ensemble approach for crude oil price forecasting.
报告摘要: As crude oil price is influenced by numerous factors, capturing its behavior precisely is quite challenging, and thus leads to the difficulty of forecasting. In this study, a deep learning ensemble approach is proposed to deal with this problem. In our approach, two techniques are utilized. One is an advanced deep neural network model named stacked denoising autoencoders (SDAE) which is used to model the nonlinear and complex relationships of oil price with its factors. The other is a powerful ensemble method named bootstrap aggregation (bagging) which generates multiple data sets for training a set of base models (SDAEs). Our approach combines the merits of these two techniques and is especially suitable for oil price forecasting. In the empirical study, the WTI crude oil price series are investigated and 198 economic series are used as exogenous variables. Our approach is tested against some competing approaches and shows superior forecasting ability that is statistically proved by three tests.
在报告中，我院博士生徐定鑫向大家展示了一种深度学习集成方法来处理 判断原油价格趋势走向的问题。报告中使用了SDAE和SDAES技术，结合这两种技术的优点来预测石油价格。
本次报告开拓了学生们的学习视野，也启发了师生们对于深度学习新方法的探究与思考，得到了更加深刻的认识。
437必赢会员中心网页版
2021年4月29日
