Prediction of Ultimate Bearing Capacity of Circularand Square Footings by Neural Network
Publish place: International Conference on Civil Engineering , Architecture and urban infrastructure
Publish Year: 1394
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
ICICA01_0004
تاریخ نمایه سازی: 27 اسفند 1394
Abstract:
For ultimate bearing capacity calculation, various Analytical – Experimental methods were proposed by Terzaghi, Mayerhof, Hansen and Vesic and the most comprehensive one in case of no axial load was proposed by Mayerhof. In this article Artificial Neural Network (ANN) is used to predict bearing capacity of circular and square shallow foundations and for this purpose Multi-layer Perceptron (MLP) is utilized. The data usedas the inputs and output of network models were parameters in Mayerhof equation and the bearing capacity calculated from this equation, respectively. Finding the best architecture of model is carried out through making different conditions such as numbers of hidden neurons and activation functions. The result of this work shows high capabilities of this kind of neural network for bearing capacity prediction
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Authors
M.M Makhmalbaf
MSc. Student of Geotechnical Engineering, Islamic Azad University, Semnan Branch, Iran
M Azimipour
MSc. Student of Water & Wastewater Engineering, Shahid Beheshti University, Iran
M Nikkhah
Assistant Professor, Department of Civil Engineering, Islamic Azad University, Semnan Branch, Iran
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