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Open AccessJournal Article

Prediction of Settlement of Shallow Footings on Granular Soils using Genetic Algorithm

Prasanth S
- 01 Jan 2015 - 
- Vol. 3, Iss: 4
TLDR
In this paper, a genetic algorithm approach is used for predicting the settlement of shallow foundations on granular soils, which can be used to fit a function to set of experimental data with a high degree of accuracy.
Abstract: 
In this paper, a genetic algorithm approach is used for predicting the settlement of shallow foundations on granular soils. The development and verification of the genetic model was done using a large database containing about 198 case histories from various published literatures. The results of the model obtained were compared with various empirical equations available for measuring settlement. The correlation of predicted datas with actual field measurements was determined and it was found out that the genetic algorithm approach can be used to fit a function to set of experimental data with a high degree of accuracy. The equation for settlement thus obtained connecting settlement and its contributing factors can be used in predicting settlements for new cases that were not used for the development of the genetic model.

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Citations
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Journal ArticleDOI

CPT-based method using hybrid artificial neural network and mathematical model to predict the load-settlement behaviour of shallow foundations

Abdelfattah Aouadj, +1 more
- 29 Apr 2020 - 
TL;DR: This paper proposes a new hybrid artificial neural network and mathematical (ANN-MATH) model to improve the prediction capability of the load-settlement behaviour of shallow foundations in sandy foundations.
Book ChapterDOI

Settlement Prediction of Shallow Foundations on Cohesionless Soil Using Hybrid PSO-ANN Approach

P. Krishna Pradeep, +2 more
TL;DR: In this article, a hybrid PSO-ANN (Particle swarm optimization-Artificial neural network) model was used for the settlement prediction of shallow foundations on cohesionless soil.
References
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Book

Genetic Programming: On the Programming of Computers by Means of Natural Selection

John R. Koza
TL;DR: This book discusses the evolution of architecture, primitive functions, terminals, sufficiency, and closure, and the role of representation and the lens effect in genetic programming.
Book

Foundation analysis and design

Joseph E. Bowles
TL;DR: In this paper, Fondation de soutenagement et al. presented a reference record for Dimensionnement Reference Record created on 2004-09-07, modified on 2016-08-08.
Journal ArticleDOI

Predicting settlement of shallow foundations using neural networks

Mohamed A. Shahin, +2 more
- 01 Sep 2002 - 
TL;DR: In this paper, artificial neural networks (ANNs) are used in an attempt to obtain more accurate settlement prediction, and the predicted settlements found by utilizing ANNs are compared with the values predicted by three of the most commonly used traditional methods.
Journal ArticleDOI

Prediction of pile bearing capacity using a hybrid genetic algorithm-based ANN

Ehsan Momeni, +3 more
- 01 Nov 2014 - 
TL;DR: Results indicate that implementation of GA-based ANN models as a highly-reliable, efficient and practical tool in predicting the pile bearing capacity is of advantage.
Journal ArticleDOI

Settlement of foundations on sand and gravel

J. B. Burland, +2 more
TL;DR: In this article, the analysis of over 200 records of settlement of foundations, tanks and embankments on sands and gravels is described, and a remarkably simple picture has emerged relating the settlement to the bearing pressure, the breadth of loaded area and the average SPT blow count or cone resistance over the depth of influence.