Artificial neural network model for predicting soil electrical resistivity-Reference-Cited by-同舟云学术

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Artificial neural network model for predicting soil electrical resistivity

Published:2015-07-27 Issue:5 Volume:29 Page:1751-1759
ISSN:1064-1246
Container-title:Journal of Intelligent & Fuzzy Systems
language:
Short-container-title:IFS

Author:

Bian Hanliang¹²,Liu Songyu¹²,Cai Guojun¹²,Tian Ling³

Affiliation:

1. Institute of Geotechnical Engineering, Southeast University, Nanjing, China

2. Jiangsu Key Laboratory of Urban Underground Engineering & Environmental Safety, Southeast University

3. Department of Traffic Engineering, Yellow River Conservancy Technical Institute, Kaifeng, China

Publisher

IOS Press

Subject

Artificial Intelligence,General Engineering,Statistics and Probability

Reference37 articles.

1. Electrical resistivity of compacted clays;Abu-Hassanein;Journal of Geotechnical Engineering,1996

2. Using complex permittivity and artificial neural networks to identify and classify copper, zinc, and lead contamination in soil;Amegashie;Canadian Geotechnical Journal,2006

3. Artificial neural network for stress–strain behavior of sandy soils: Knowledge based verification;Banimahd;Computers and Geotechnics,2005

4. Beale MH Hagan MT Demuth HB 2010 Neural Network Toolbox 7. User’s Guide, MathWorks

5. Identification of soil strata based on general regression neural network model from CPTU data;Cai;Marine Georesources & Geotechnology,2015

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4. A Review on Artificial Intelligence Based Parameter Forecasting for Soil-Water Content;Machine Learning and Data Mining in Pattern Recognition;2016

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