159 related articles for article (PubMed ID: 36262133)
1. Empirical mode decomposition using deep learning model for financial market forecasting.
Jin Z; Jin Y; Chen Z
PeerJ Comput Sci; 2022; 8():e1076. PubMed ID: 36262133
[TBL] [Abstract][Full Text] [Related]
2. Mid-long term forecasting of reservoir inflow using the coupling of time-varying filter-based empirical mode decomposition and gated recurrent unit.
Wang X; Zhang S; Qiao H; Liu L; Tian F
Environ Sci Pollut Res Int; 2022 Dec; 29(58):87200-87217. PubMed ID: 35804225
[TBL] [Abstract][Full Text] [Related]
3. Forecasting stochastic neural network based on financial empirical mode decomposition.
Wang J; Wang J
Neural Netw; 2017 Jun; 90():8-20. PubMed ID: 28364677
[TBL] [Abstract][Full Text] [Related]
4. Forecasting China carbon price using an error-corrected secondary decomposition hybrid model integrated fuzzy dispersion entropy and deep learning paradigm.
Yun P; Zhou Y; Liu C; Wu Y; Pan D
Environ Sci Pollut Res Int; 2024 Mar; 31(11):16530-16553. PubMed ID: 38321281
[TBL] [Abstract][Full Text] [Related]
5. Forecasting outpatient visits using empirical mode decomposition coupled with back-propagation artificial neural networks optimized by particle swarm optimization.
Huang D; Wu Z
PLoS One; 2017; 12(2):e0172539. PubMed ID: 28222194
[TBL] [Abstract][Full Text] [Related]
6. Research on Deformation Prediction of VMD-GRU Deep Foundation Pit Based on PSO Optimization Parameters.
Liu R; Zhang Q; Jiang F; Zhou J; He J; Mao Z
Materials (Basel); 2024 May; 17(10):. PubMed ID: 38793264
[TBL] [Abstract][Full Text] [Related]
7. Using the hybrid EMD-BPNN model to predict the incidence of HIV in Dalian, Liaoning Province, China, 2004-2018.
An Q; Wu J; Meng J; Zhao Z; Bai JJ; Li X
BMC Infect Dis; 2022 Jan; 22(1):102. PubMed ID: 35093010
[TBL] [Abstract][Full Text] [Related]
8. Stock Price Forecasting by a Deep Convolutional Generative Adversarial Network.
Staffini A
Front Artif Intell; 2022; 5():837596. PubMed ID: 35187477
[TBL] [Abstract][Full Text] [Related]
9. Application of empirical mode decomposition to improve deep learning for US GDP data forecasting.
Lin SL
Heliyon; 2022 Jan; 8(1):e08748. PubMed ID: 35146147
[TBL] [Abstract][Full Text] [Related]
10. An LSTM and GRU based trading strategy adapted to the Moroccan market.
Touzani Y; Douzi K
J Big Data; 2021; 8(1):126. PubMed ID: 34603936
[TBL] [Abstract][Full Text] [Related]
11. PM2.5 concentration forecasting at surface monitoring sites using GRU neural network based on empirical mode decomposition.
Huang G; Li X; Zhang B; Ren J
Sci Total Environ; 2021 May; 768():144516. PubMed ID: 33453525
[TBL] [Abstract][Full Text] [Related]
12. Predicting regional carbon price in China based on multi-factor HKELM by combining secondary decomposition and ensemble learning.
Hu B; Cheng Y
PLoS One; 2023; 18(12):e0285311. PubMed ID: 38085727
[TBL] [Abstract][Full Text] [Related]
13. Carbon price prediction for China's ETS pilots using variational mode decomposition and optimized extreme learning machine.
Chai S; Zhang Z; Zhang Z
Ann Oper Res; 2021 Nov; ():1-22. PubMed ID: 34812214
[TBL] [Abstract][Full Text] [Related]
14. Application of empirical mode decomposition with local linear quantile regression in financial time series forecasting.
Jaber AM; Ismail MT; Altaher AM
ScientificWorldJournal; 2014; 2014():708918. PubMed ID: 25140343
[TBL] [Abstract][Full Text] [Related]
15. Assessment of hybrid machine learning algorithms using TRMM rainfall data for daily inflow forecasting in Três Marias Reservoir, eastern Brazil.
Gomaa E; Zerouali B; Difi S; El-Nagdy KA; Santos CAG; Abda Z; Ghoneim SSM; Bailek N; Silva RMD; Rajput J; Ali E
Heliyon; 2023 Aug; 9(8):e18819. PubMed ID: 37593632
[TBL] [Abstract][Full Text] [Related]
16. Network Security Situation Prediction Model Based on EMD and ELPSO Optimized BiGRU Neural Network.
Zhang B; Jia M; Xu J; Zhao W; Deng L
Comput Intell Neurosci; 2022; 2022():6031129. PubMed ID: 35774431
[TBL] [Abstract][Full Text] [Related]
17. Carbon price forecasting using multiscale nonlinear integration model coupled optimal feature reconstruction with biphasic deep learning.
Wang J; Cheng Q; Sun X
Environ Sci Pollut Res Int; 2022 Dec; 29(57):85988-86004. PubMed ID: 34453680
[TBL] [Abstract][Full Text] [Related]
18. Multiscaled Neural Autoregressive Distributed Lag: A New Empirical Mode Decomposition Model for Nonlinear Time Series Forecasting.
Saâdaoui F; Messaoud OB
Int J Neural Syst; 2020 Aug; 30(8):2050039. PubMed ID: 32588684
[TBL] [Abstract][Full Text] [Related]
19. Applying attention-based BiLSTM and technical indicators in the design and performance analysis of stock trading strategies.
Lee MC; Chang JW; Yeh SC; Chia TL; Liao JS; Chen XM
Neural Comput Appl; 2022; 34(16):13267-13279. PubMed ID: 35106029
[TBL] [Abstract][Full Text] [Related]
20. Enhanced rainfall prediction performance via hybrid empirical-singular-wavelet-fuzzy approaches.
Küllahcı K; Altunkaynak A
Environ Sci Pollut Res Int; 2023 Apr; 30(20):58090-58108. PubMed ID: 36976466
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
