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
基金
中国国家自然科学基金;
关键词
Compilation and indexing terms; Copyright 2024 Elsevier Inc;
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
收藏
相关论文
共 50 条
  • [11] A hybrid CNN-LSTM model for typhoon formation forecasting
    Chen, Rui
    Wang, Xiang
    Zhang, Weimin
    Zhu, Xiaoyu
    Li, Aiping
    Yang, Chao
    [J]. GEOINFORMATICA, 2019, 23 (03) : 375 - 396
  • [12] Hybrid wind speed forecasting using ICEEMDAN and transformer model with novel loss function
    Bommidi, Bala Saibabu
    Teeparthi, Kiran
    Kosana, Vishalteja
    [J]. ENERGY, 2023, 265
  • [13] Carbon futures price forecasting based with ARIMA-CNN-LSTM model
    Ji, Lei
    Zou, Yingchao
    He, Kaijian
    Zhu, Bangzhu
    [J]. 7TH INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY AND QUANTITATIVE MANAGEMENT (ITQM 2019): INFORMATION TECHNOLOGY AND QUANTITATIVE MANAGEMENT BASED ON ARTIFICIAL INTELLIGENCE, 2019, 162 : 33 - 38
  • [14] ANN, LSTM, and SVR for Gold Price Forecasting
    Yang, Jiacheng
    De Montigny, Denis
    Treleaven, Philip
    [J]. 2022 IEEE SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE FOR FINANCIAL ENGINEERING AND ECONOMICS (CIFER), 2022,
  • [15] 小波包能量谱结合LSTM-CNN-CBAM的旋转机械故障诊断
    郭文博
    石刚
    刘晓松
    [J]. 组合机床与自动化加工技术, 2022, (10) : 69 - 73
  • [16] A Novel Hybrid Model for Financial Forecasting Based on CEEMDAN-SE and ARIMA-CNN-LSTM
    Dong, Zefan
    Zhou, Yonghui
    [J]. MATHEMATICS, 2024, 12 (16)
  • [17] Short-term wind speed forecasting based on a hybrid model of ICEEMDAN, MFE, LSTM and informer
    Wang Xinxin
    Shen Xiaopan
    Ai Xueyi
    Li Shijia
    [J]. PLOS ONE, 2023, 18 (09):
  • [18] Forecasting turning points in stock price by applying a novel hybrid CNN-LSTM-ResNet model fed by 2D segmented images
    Khodaee, Pouya
    Esfahanipour, Akbar
    Taheri, Hassan Mehtari
    [J]. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2022, 116
  • [19] A Forecasting Model of Ionospheric foF2 Using the LSTM Network Based on ICEEMDAN Decomposition
    Shi, Yafei
    Yang, Cheng
    Wang, Jian
    Zhang, Zhigang
    Meng, Fanyi
    Bai, Hongmei
    [J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2023, 61
  • [20] A Forecasting Model of Ionospheric foF2 Using the LSTM Network Based on ICEEMDAN Decomposition
    Shi, Yafei
    Yang, Cheng
    Wang, Jian
    Zhang, Zhigang
    Meng, Fanyi
    Bai, Hongmei
    [J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2023, 61 : 1 - 16