High Performance Computing and Artificial Intelligence for Geosciences

In total, this Special Issue includes 11 papers. Firstly, Qi et al. conducted research on the large-scale non-uniform parallel solution of the two-dimensional Saint-Venant equations for flood behavior modeling. Zhang et al. proposed an efficient deep learning-based mineral identification method. Sub...

Полное описание

Сохранить в:

Библиографические подробности
Формат:	Online
Язык:	английский
Опубликовано:	MDPI - Multidisciplinary Digital Publishing Institute 2023
Предметы:	Saint-Venant equations finite difference method parallel computing heterogeneous computing deep learning image enhancement mineral identification convolutional neural networks BERT named entity recognition geological news CRF semantic segmentation PSPNet landslide submarine landslide machine learning hazard susceptibility spatial distribution ZTEM 2D forward modeling inversion parallel algorithm tipper disaster precursor identification early warning association rule mining particle swarm optimization k-means clustering Apriori algorithm gray relation analysis transformer photovoltaic power forecasting satellite images LICOM meteorological model parallel optimization time series missing data tensor completion autoregressive norm displacement prediction GeoMAN model gross primary productivity attention mechanism interdisciplinary n/a thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries
Online-ссылка:	ONIX_20230808_9783036581804_14
Метки:	Добавить метку Нет меток, Требуется 1-ая метка записи!

Ваш комментарий будет первым!

High Performance Computing and Artificial Intelligence for Geosciences

Схожие документы