Flexural Buckling of Concrete-Filled Aluminium Alloy CHS Columns: Numerical Modelling and Design

Author(s):  
Evangelia Georgantzia ◽  
Michaela Gkantou
2020 ◽  
Vol 155 ◽  
pp. 106926
Author(s):  
Zhongxing Wang ◽  
Yuanqing Wang ◽  
Xiang Yun ◽  
Ying Zhang ◽  
Zhiqiang Li ◽  
...  

Author(s):  
Bulent Haznedar ◽  
Rabia Bayraktar ◽  
Melih Yayla ◽  
Mustafa Diyar Demirkol

In this study, we propose a simulated annealing algorithm (SA) to train an adaptive neurofuzzy inference system (ANFIS). We performed different types of optimization algorithms such as genetic algorithm (GA), SA and artificial bee colony algorithm on two different problem types. Then, we measured the performance of these algorithms. First, we applied optimization algorithms on eight numerical benchmark functions which are sphere, axis parallel hyper-ellipsoid, Rosenbrock, Rastrigin, Schwefel, Griewank, sum of different powers and Ackley functions. After that, the training of ANFIS is carried out by mentioned optimization algorithms to predict the strength of heat-treated fine-drawn aluminium composite columns defeated by flexural bending. In summary, the accuracy of the proposed soft computing model was compared with the accuracy of the results of existing methods in the literature. It is seen that the training of ANFIS with the SA has more accuracy.   Keywords: Soft computing, ANFIS, simulated annealing, flexural buckling, aluminium alloy columns.


2018 ◽  
Vol 130 ◽  
pp. 1-11 ◽  
Author(s):  
Weigang Chen ◽  
Hua Deng ◽  
Shilin Dong ◽  
Zhongyi Zhu

2004 ◽  
Vol 17 (6) ◽  
pp. 321-331 ◽  
Author(s):  
X. Yang ◽  
X. Huang ◽  
X. Dai ◽  
J. Campbell ◽  
J. Tatler

2021 ◽  
Vol 242 ◽  
pp. 112546
Author(s):  
Evangelia Georgantzia ◽  
Shafayat Bin Ali ◽  
Michaela Gkantou ◽  
George S. Kamaris ◽  
Kunal D. Kansara ◽  
...  

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