Locating a New Drainage Well by Optimization of a Back Propagation Model-Reference-Cited by-同舟云学术

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Locating a New Drainage Well by Optimization of a Back Propagation Model

Published:2019-01-31 Issue:2 Volume:38 Page:342-352
ISSN:1025-9112
Container-title:Mine Water and the Environment
language:en
Short-container-title:Mine Water Environ

Author:

Maknouni Gilani Saeid,Zare Mohammad,Raeisi Ezzatollah

Publisher

Springer Science and Business Media LLC

Subject

Geotechnical Engineering and Engineering Geology,Water Science and Technology

Link

http://link.springer.com/article/10.1007/s10230-019-00593-6/fulltext.html

Reference41 articles.

1. Adamowski J, Fung Chan H (2012) A wavelet neural network conjunction model for groundwater level forecasting. J Hydrol 407(1–4):28–40

2. Al-Ruwaih FM, Ben-Essa SA (2004) Multi-well and multi-tracer tests to characterize the groundwater aquifers in southern Kuwait. Bull Eng Geol Environ 63:57–70

3. Aminian K, Ameri S (2005) Application of artificial neural networks for reservoir characterization with limited data. J Petrol Sci Eng 49:212–222

4. Banerjee P, Singh VS, Chattopadhyay K, Chandra PC, Singh B (2011) Artificial neural network model as a potential alternative for GW salinity forecasting. J Hydrol 398(3–4):212–220

5. Bhatt A, Helle HB (2002) Committee neural networks for porosity and permeability prediction from well logs. Geophys Prospect 50:645–660

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1. Reservoir Prediction Model via the Fusion of Optimized Long Short-Term Memory Network (LSTM) and Bidirectional Random Vector Functional Link (RVFL);Electronics;2022-10-17

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