Densely Connected Squeeze‐and‐Excitation Convolutional Encoder‐Decoder Networks for Identifying Preferential Channels in Highly Heterogeneous Porous Media-Reference-Cited by-同舟云学术

Densely Connected Squeeze‐and‐Excitation Convolutional Encoder‐Decoder Networks for Identifying Preferential Channels in Highly Heterogeneous Porous Media

Published:2022-09 Issue:9 Volume:58 Page:
ISSN:0043-1397
Container-title:Water Resources Research
language:en
Short-container-title:Water Resources Research

Author:

Zhou Zhengkun¹²^ORCID,Shi Liangsheng¹^ORCID,Zha Yuanyuan¹^ORCID,Wang Shuixian²,Xu Baokun³,Tian Lei²^ORCID,Zhang Lanhui²,Tian Jie²^ORCID,Yang Ruiting⁴

Affiliation:

1. State Key Laboratory of Water Resources and Hydropower Engineering Science Wuhan University Wuhan China

2. Key Laboratory of Western China's Environmental Systems (Ministry of Education) College of Earth and Environmental Sciences Lanzhou University Lanzhou China

3. Agricultural Water Conservancy Department Changjiang River Scientific Research Institute Wuhan China

4. PowerChina Guiyang Engineering Corporation Limited Guiyang China

Publisher

American Geophysical Union (AGU)

Subject

Water Science and Technology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1029/2021WR031429

Reference43 articles.

1. An Entrogram‐Based Approach to Describe Spatial Heterogeneity With Applications to Solute Transport in Porous Media

2. Mechanisms, Upscaling, and Prediction of Anomalous Dispersion in Heterogeneous Porous Media

3. Solute transport in aquifers of arbitrary variability: A time-domain random walk formulation

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