168 related articles for article (PubMed ID: 22391234)
1. A morphological perceptron with gradient-based learning for Brazilian stock market forecasting.
Araújo Rde A
Neural Netw; 2012 Apr; 28():61-81. PubMed ID: 22391234
[TBL] [Abstract][Full Text] [Related]
2. Hybrid intelligent methodology to design translation invariant morphological operators for Brazilian stock market prediction.
Araújo Rde A
Neural Netw; 2010 Dec; 23(10):1238-51. PubMed ID: 20643527
[TBL] [Abstract][Full Text] [Related]
3. An evolutionary morphological approach for software development cost estimation.
Araújo Rde A; Oliveira AL; Soares S; Meira S
Neural Netw; 2012 Aug; 32():285-91. PubMed ID: 22560678
[TBL] [Abstract][Full Text] [Related]
4. A learning rule for very simple universal approximators consisting of a single layer of perceptrons.
Auer P; Burgsteiner H; Maass W
Neural Netw; 2008 Jun; 21(5):786-95. PubMed ID: 18249524
[TBL] [Abstract][Full Text] [Related]
5. A novel stock forecasting model based on High-order-fuzzy-fluctuation Trends and Back Propagation Neural Network.
Guan H; Dai Z; Zhao A; He J
PLoS One; 2018; 13(2):e0192366. PubMed ID: 29420584
[TBL] [Abstract][Full Text] [Related]
6. Stock Market Forecasting Using Restricted Gene Expression Programming.
Yang B; Zhang W; Wang H
Comput Intell Neurosci; 2019; 2019():7198962. PubMed ID: 30867661
[TBL] [Abstract][Full Text] [Related]
7. Forecasting financial asset processes: stochastic dynamics via learning neural networks.
Giebel S; Rainer M
Bull Soc Sci Med Grand Duche Luxemb; 2010; Spec No 1(1):91-107. PubMed ID: 20653181
[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. Reinforced two-step-ahead weight adjustment technique for online training of recurrent neural networks.
Chang LC; Chen PA; Chang FJ
IEEE Trans Neural Netw Learn Syst; 2012 Aug; 23(8):1269-78. PubMed ID: 24807523
[TBL] [Abstract][Full Text] [Related]
10. 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]
11. Modular learning models in forecasting natural phenomena.
Solomatine DP; Siek MB
Neural Netw; 2006 Mar; 19(2):215-24. PubMed ID: 16531005
[TBL] [Abstract][Full Text] [Related]
12. Adaptive time-variant models for fuzzy-time-series forecasting.
Wong WK; Bai E; Chu AW
IEEE Trans Syst Man Cybern B Cybern; 2010 Dec; 40(6):1531-42. PubMed ID: 20335097
[TBL] [Abstract][Full Text] [Related]
13. Correcting and combining time series forecasters.
Firmino PR; de Mattos Neto PS; Ferreira TA
Neural Netw; 2014 Feb; 50():1-11. PubMed ID: 24239986
[TBL] [Abstract][Full Text] [Related]
14. A comparative study of autoregressive neural network hybrids.
Taskaya-Temizel T; Casey MC
Neural Netw; 2005; 18(5-6):781-9. PubMed ID: 16085389
[TBL] [Abstract][Full Text] [Related]
15. Random neural networks with synchronized interactions.
Gelenbe E; Timotheou S
Neural Comput; 2008 Sep; 20(9):2308-24. PubMed ID: 18386985
[TBL] [Abstract][Full Text] [Related]
16. Storage and recall capabilities of fuzzy morphological associative memories with adjunction-based learning.
Valle ME; Sussner P
Neural Netw; 2011 Jan; 24(1):75-90. PubMed ID: 20870391
[TBL] [Abstract][Full Text] [Related]
17. Artificial neural networks applied to forecasting time series.
Montaño Moreno JJ; Palmer Pol A; Muñoz Gracia P
Psicothema; 2011 Apr; 23(2):322-9. PubMed ID: 21504688
[TBL] [Abstract][Full Text] [Related]
18. Volatility forecasts of stock index futures in China and the US-A hybrid LSTM approach.
Chen X; Hu Y
PLoS One; 2022; 17(7):e0271595. PubMed ID: 35901029
[TBL] [Abstract][Full Text] [Related]
19. Comparing Artificial Neural Network Architectures for Brazilian Stock Market Prediction.
Teixeira Zavadzki de Pauli S; Kleina M; Bonat WH
Ann Data Sci; 2020; 7(4):613-628. PubMed ID: 38624383
[TBL] [Abstract][Full Text] [Related]
20. Learning curves for stochastic gradient descent in linear feedforward networks.
Werfel J; Xie X; Seung HS
Neural Comput; 2005 Dec; 17(12):2699-718. PubMed ID: 16212768
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
