RESEARCH ARTICLE
Deep Pile Foundation Settlement Prediction Using Neurofuzzy Networks
Hussein Y. Aziz*
Article Information
Identifiers and Pagination:
Year: 2014Volume: 8
First Page: 78
Last Page: 104
Publisher ID: TOCIEJ-8-78
DOI: 10.2174/1874149501408010078
Article History:
Received Date: 9/1/2014Revision Received Date: 6/5/2014
Acceptance Date: 7/5/2014
Electronic publication date: 13/6/2014
Collection year: 2014
open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
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.