Mapping of hydraulic transmissivity field from inversion of tracer test data using convolutional neural networks. CNN-2T
Author:
Publisher
Elsevier BV
Subject
Water Science and Technology
Reference58 articles.
1. Tracer model identification using artificial neural networks;Akin;Water Resour. Res.,2005
2. Apolinario M., Huaman Bustamante S., Morales G., Diaz D. (2019). Estimation of 2D Velocity Model using Acoustic Signals and Convolutional Neural Networks. 2019 IEEE XXVI International Conference on Electronics, Electrical Engineering and Computing (INTERCON).
3. SegNet: a deep convolutional encoder-decoder architecture for image segmentation;Badrinarayanan;IEEE Trans. Pattern Anal. Mach. Intell.,2017
4. Estimating geostatistical parameters and spatially-variable hydraulic conductivity within a catchment system using an ensemble smoother;Bailey;Hydrol. Earth Syst. Sci.,2012
5. Aquifer parameters determination for large diameter wells using neural network approach;Balkhair;J. Hydrol.,2002
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