Forecasting gold price using a novel hybrid model with ICEEMDAN and LSTM-CNN-CBAM

被引：0

作者：

Liang, Yanhui ^{[1
]}

Lin, Yu ^{[2
]}

Lu, Qin ^{[2
]}

机构：

[1] School of Management Science, Chengdu University of Technology, Chengdu,610059, China

[2] School of Business, Chengdu University of Technology, Chengdu,610059, China

来源：

Expert Systems with Applications | 2022年 / 206卷

基金：

中国国家自然科学基金;

关键词：

D O I：

暂无

中图分类号：

学科分类号：

摘要：

Brain - Convolution - Convolutional neural networks - Decomposition methods - Forecasting - Long short-term memory - Spurious signal noise

引用

共 50 条

[1] Forecasting gold price using a novel hybrid model with ICEEMDAN and LSTM-CNN-CBAM
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[J]. EXPERT SYSTEMS WITH APPLICATIONS, 2022, 206
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