An advanced spatio-temporal convolutional recurrent neural network for storm surge predictions

In this research paper, we study the capability of artificial neural network models to emulate storm surge based on the storm track/size/intensity history, leveraging a database of synthetic storm simulations. Traditionally, computational fluid dynamics (CFD) solvers are employed to numerically solv...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	Neural computing & applications Ročník 35; číslo 26; s. 18971 - 18987
Hlavní autoři:	Adeli, Ehsan, Sun, Luning, Wang, Jianxun, Taflanidis, Alexandros A.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	London Springer London 01.09.2023 Springer Nature B.V
Témata:	Artificial Intelligence Artificial neural networks Coders Computational Biology/Bioinformatics Computational fluid dynamics Computational Science and Engineering Computer Science Data Mining and Knowledge Discovery Gaussian process Image Processing and Computer Vision Mathematical models Neural networks Nodes Original Article Partial differential equations Probability and Statistics in Computer Science Recurrent neural networks Solvers Storm surges Storms Tidal waves Time series Advanced neural networks Recurrent neural networks Storm surge prediction Convolutional neural networks
ISSN:	0941-0643, 1433-3058
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Buďte první, kdo okomentuje tento záznam!