Automatic soil classification method from CPTU data based on convolutional neural networks

Study on soil classification using piezocone penetration test (CPTU) has accumulated a considerable number of research findings. Inspired by the rapid developments in machine learning, this technique has provided new ideas for the interpretation of CPTU data. However, due to the subjectivity of feat...

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Veröffentlicht in:	Bulletin of engineering geology and the environment 2024-08, Vol.83 (8), p.319, Article 319
Hauptverfasser:	Liu, Wenyuan, Tong, Liyuan, Sun, Yinjuan, Wu, Hao, Yan, Xin, Liu, Songyu
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Algorithms Artificial intelligence Artificial neural networks Classification Deep learning Earth and Environmental Science Earth Sciences Foundations Friction Geoecology/Natural Processes Geoengineering Geotechnical Engineering & Applied Earth Sciences Hydraulics Learning algorithms Machine learning Methods Nature Conservation Neural networks Noise prediction Noise reduction Original Paper Performance prediction Soil Soil classification Soil layers Soil penetration tests Soil testing Soil types Soils Stratification Wavelet transforms
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