Tracked shipping to New Zealand with premium packaging for just NZ$15 

Ship to
New Zealand
0

My Account

  • argentina
  • chile
  • colombia
  • españa
  • méxico
  • perú
  • estados unidos
  • internacional

menu

Select your country

Americas

Europe

Rest of the world

portada High Performance Computing and Artificial Intelligence for Geosciences
Type
Physical Book
Publisher
Author
Language
English
Pages
188
Format
Hardcover
Dimensions
24.4 x 17.0 x 1.6 cm
Weight
0.61 kg.
ISBN13
9783036581804
Categories

High Performance Computing and Artificial Intelligence for Geosciences

Wang, Yuzhu ; Jiang, Jinrong ; Wang, Yangang (Author) · Mdpi AG · Hardcover

High Performance Computing and Artificial Intelligence for Geosciences - Wang, Yuzhu ; Jiang, Jinrong ; Wang, Yangang

New Book Imported to New Zealand
Delivery: 11 Aug - 18 Aug Shipping: 4 to 5 business days.
NZ$ 155.96
Import costs and 15% GST included in the price ✅
NZ$ 155.96

Choose the list to add your product or create one New List

Go to My Wishlists
Calculate shipping cost

Synopsis "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. Subsequently, Huang et al. proposed a named entity recognition method for geological news based on BERT model. Yang et al. proposed an automatic landslide identification method to solve the problem of the time-consuming nature and low efficiency of traditional landslide identification methods. Du et al. analyzed the potential of unsupervised machine learning methods for submarine landslide prediction. Wang et al. performed parallel computations on the inversion algorithm of the two-dimensional ZTEM. Xu et al. used the sliding window method and gray relational analysis to extract features from multi-source real-time monitoring data of landslides. Furthermore, Cao et al. proposed a new method called dual encoder transform (DualET) for the short-term prediction of photovoltaic power. Hao et al. conducted a series of parallel optimizations and large-scale parallel simulations on the high-resolution ocean model. Wang et al. proposed a time series prediction model for landslide displacements using mean-based low-rank autoregressive tensor completion. Finally, Yang et al. developed a measure of site-level gross primary productivity (GPP) using the GeoMAN model.

Customers reviews

More customer reviews
  • 0% (0)
  • 0% (0)
  • 0% (0)
  • 0% (0)
  • 0% (0)

Frequently Asked Questions about the Book

Is the book original?

All books in our catalog are Original.

In what language is the book written?

The book is written in English.

What is the format of this book?

The binding of this edition is Hardcover.

Questions and Answers about the Book

Do you have a question about the book? Login to be able to add your own question.

Opinions about Bookdelivery

More customer reviews