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Stability assessment of homogeneous slopes loaded with mobile tracked cranes—An artificial neural network approach


Stability assessment of homogeneous slopes loaded with mobile tracked cranes—An artificial neural network approach

Ai, Xin and Zsaki, Attila Michael (2017) Stability assessment of homogeneous slopes loaded with mobile tracked cranes—An artificial neural network approach. Cogent Engineering, 4 (1). pp. 1-13. ISSN 2331-1916

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Official URL: http://dx.doi.org/10.1080/23311916.2017.1360236


Construction projects often involve the use of mobile crawler cranes to excavate, backfill, dredge or move material and equipment on or near slopes. Crane manufacturers often only provide guidelines for the safe operation of cranes with respect to over tipping. However, the complex interaction of many variables such as the crane, its load, the slope geometry and its geotechnical properties can create slope instability. In this study, an artificial neural network was developed to predict the stability of these slopes loaded by mobile cranes. The neural network was built and trained using a set of slope stability models that were constructed using the above parameters via Monte Carlo sampling. The trained network was capable of predicting the factor of safety of a loaded slope and the location of the critical failure surface with relatively low error. In addition, the quality of the network’s output was investigated using multiple metrics, such as the correlation ratio or the mean squared error and quite high correlation was achieved. Thus, the predicting capabilities of the network can be used with confidence to aid the positioning of mobile cranes on slopes without a need to perform slope stability analysis for each scenario.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Building, Civil and Environmental Engineering
Item Type:Article
Authors:Ai, Xin and Zsaki, Attila Michael
Journal or Publication:Cogent Engineering
Date:31 July 2017
  • Concordia Open Access Author Fund
Digital Object Identifier (DOI):10.1080/23311916.2017.1360236
Keywords:slope stability, crawler crane, artificial neural network
ID Code:982892
Deposited By: Danielle Dennie
Deposited On:30 Aug 2017 15:02
Last Modified:18 Jan 2018 17:55


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