Cargando…
Forecasting stock prices with a feature fusion LSTM-CNN model using different representations of the same data
Forecasting stock prices plays an important role in setting a trading strategy or determining the appropriate timing for buying or selling a stock. We propose a model, called the feature fusion long short-term memory-convolutional neural network (LSTM-CNN) model, that combines features learned from...
Autores principales: | Kim, Taewook, Kim, Ha Young |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6377125/ https://www.ncbi.nlm.nih.gov/pubmed/30768647 http://dx.doi.org/10.1371/journal.pone.0212320 |
Ejemplares similares
-
LSTM-based sentiment analysis for stock price forecast
por: Ko, Ching-Ru, et al.
Publicado: (2021) -
Data science approach to stock prices forecasting in Indonesia during Covid-19 using Long Short-Term Memory (LSTM)
por: Budiharto, Widodo
Publicado: (2021) -
Research on DNA-Binding Protein Identification Method Based on LSTM-CNN Feature Fusion
por: Lu, Weizhong, et al.
Publicado: (2022) -
NLOS Identification in WLANs Using Deep LSTM with CNN Features
por: Nguyen, Viet-Hung, et al.
Publicado: (2018) -
CNN-Bi-LSTM: A Complex Environment-Oriented Cattle Behavior Classification Network Based on the Fusion of CNN and Bi-LSTM
por: Gao, Guohong, et al.
Publicado: (2023)