Deep Pile Foundation Settlement Prediction Using Neurofuzzy Networks
Auteur(s): |
Hussein Y. Aziz
|
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Médium: | article de revue |
Langue(s): | anglais |
Publié dans: | The Open Civil Engineering Journal, juin 2015, n. 1, v. 8 |
Page(s): | 78-104 |
DOI: | 10.2174/1874149501408010078 |
Abstrait: |
A NeuroFuzzy System (NFS) is one of the most commonly used systems in the real life problems because it has explicit and transparency which results from the fuzzy systems, with the learning and generalization capabilities from the dynamic behavior of the neural networks. It is one of the most successful systems, which introduced to decrement the fuzzy rules that constituting the underlying model. This system has a high efficiency; it gives good results in high speed. The NFS used in this study to predict the settlement of deep pile foundations. The results obtained from this system give good agreement and high precious for prediction of settlement compared with hyperbolic model and statistical regression analysis. Also, this scenario can be applied for similar or more complicated problems in the geotechnical engineering. |
Copyright: | © 2015 Hussein Y. Aziz |
License: | Cette oeuvre a été publiée sous la license Creative Commons Attribution 4.0 (CC-BY 4.0). Il est autorisé de partager et adapter l'oeuvre tant que l'auteur est crédité et la license est indiquée (avec le lien ci-dessus). Vous devez aussi indiquer si des changements on été fait vis-à-vis de l'original. |
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