Results 81 to 90 of about 1,361 (122)

An Optimized Artificial Neural Network Structure to Predict Clay Sensitivity in a High Landslide Prone Area Using Piezocone Penetration Test (CPTu) Data: A Case Study in Southwest of Sweden

Geotechnical and Geological Engineering, 2016
Application of artificial neural networks (ANN) in various aspects of geotechnical engineering problems such as site characterization due to have difficulty to solve or interrupt through conventional approaches has demonstrated some degree of success. In the current paper a developed and optimized five layer feed-forward back-propagation neural network
Abbas Abbaszadeh Shahri   +1 more
exaly   +4 more sources

Cavity expansion-based interpretation of piezocone penetration test (CPTu) data in clays

Geotechnique
A cavity expansion-based method is proposed in this paper to correlate the relevant findings with the piezocone penetration test (CPTu) data in clays.
Pin-Qiang Mo   +2 more
exaly   +3 more sources

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