Cargando…
A Variational Bayesian Deep Network with Data Self-Screening Layer for Massive Time-Series Data Forecasting
Compared with mechanism-based modeling methods, data-driven modeling based on big data has become a popular research field in recent years because of its applicability. However, it is not always better to have more data when building a forecasting model in practical areas. Due to the noise and confl...
Autores principales: | Jin, Xue-Bo, Gong, Wen-Tao, Kong, Jian-Lei, Bai, Yu-Ting, Su, Ting-Li |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8947458/ https://www.ncbi.nlm.nih.gov/pubmed/35327846 http://dx.doi.org/10.3390/e24030335 |
Ejemplares similares
-
Modeling and Analysis of Data-Driven Systems through Computational Neuroscience Wavelet-Deep Optimized Model for Nonlinear Multicomponent Data Forecasting
por: Jin, Xue-Bo, et al.
Publicado: (2021) -
Probabilistic forecasting and Bayesian data assimilation
por: Reich, Sebastian, et al.
Publicado: (2015) -
Bayesian Sigmoid-Type Time Series Forecasting with Missing Data for Greenhouse Crops
por: Kocian, Alexander, et al.
Publicado: (2020) -
Applied Bayesian forecasting and time series analysis
por: Pole, Andy, et al.
Publicado: (1994) -
Applied Bayesian forecasting and times series analysis /
por: Pole, Andy
Publicado: (1994)