Novel metaheuristic classification approach in developing mathematical model-based solutions predicting failure in shallow footing - Engineering with Computers

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ID: 268679
2019
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Abstract
This study evaluated and compared several novel classification approaches to develop the most reliable stability model-based solution in the prediction of shallow footing’s allowable settlement. By applying the biogeography-based algorithm, this study presents an optimized metaheuristic classification approach with mathematical-based multi-layer perceptron neural network and fuzzy inference system to achieve a better assessment of the recognition of a complex failure phenomenon. By the contribution of a large number of finite element simulation, and considering seven key factors, the settlement of a shallow footing placed on a two-layered soil was measured as the target variable. Then, to change into the classification method, two overall situations of stability or failure were considered for the proposed soil layer. The ensemble of BBO–MLP and BBO–FIS are developed, and the results are evaluated by well-known accuracy indices. The results showed that employing BBO helps both MLP and FIS to have a better analysis. Besides, referring to the obtained total ranking scores of 6, 5, 11, and 8, respectively, for the MLP, FIS, BBO–MLP, and BBO–FIS, the BBO–MLP found to be the most accurate model, followed by BBO–FIS, MLP, and FIS.
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hossein2019engineeringnovel Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Moayedi, Hossein;Nguyen, Hoang;Rashid, Ahmad Safuan A.;Moayedi, Hossein;Nguyen, Hoang;Rashid, Ahmad Safuan A.;
Journal engineering with computers
Year 2019
DOI
doi:10.1007/s00366-019-00819-9
URL
https://dx.doi.org/10.1007/s00366-019-00819-9
Keywords
Control classical mechanics mathematical and computational engineering computer-aided engineering (cad cae) and design math. applications in chemistry systems theory calculus of variations and optimal control; optimization

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