A damage identification method for truss structures using a flexibility-based damage probability index and differential evolution algorithm

2015 ◽  
Vol 24 (8) ◽  
pp. 1303-1322 ◽  
Author(s):  
S. M. Seyedpoor ◽  
M. Montazer
Keyword(s):  
Differential Evolution ◽  
Damage Identification ◽  
Differential Evolution Algorithm ◽  
Truss Structures ◽  
Identification Method ◽  
Damage Probability ◽  
Evolution Algorithm ◽  
Probability Index

scholarly journals Sequential Parameter Identification of Fractional-Order Duffing System Based on Differential Evolution Algorithm

2017 ◽  
Vol 2017 ◽  
pp. 1-13
Author(s):  
Li Lai ◽  
Yuan-Dong Ji ◽  
Su-Chuan Zhong ◽  
Lu Zhang
Keyword(s):  
Differential Evolution ◽  
Parameter Identification ◽  
Fractional Order ◽  
Dynamic Properties ◽  
Differential Evolution Algorithm ◽  
Duffing System ◽  
Identification Method ◽  
System A ◽  
Evolution Algorithm ◽  
Search Capability

Using the dynamic properties of fractional-order Duffing system, a sequential parameter identification method based on differential evolution optimization algorithm is proposed for the fractional-order Duffing system. Due to the step by step parameter identification method, the dimension of parameter identification of each step is greatly reduced and the search capability of the differential evolution algorithm has been greatly improved. The simulation results show that the proposed method has higher convergence reliability and accuracy of identification and also has high robustness in the presence of measurement noise.

scholarly journals Optimization of steel roof trusses using machine learning-assisted differential evolution

2021 ◽  
Vol 15 (4) ◽  
pp. 99-110
Author(s):  
Nguyen Tran Hieu ◽  
Nguyen Quoc Cuong ◽  
Vu Anh Tuan
Keyword(s):  
Differential Evolution ◽  
Computational Cost ◽  
Differential Evolution Algorithm ◽  
Truss Structures ◽  
De Algorithm ◽  
Design Variables ◽  
Evolution Algorithm ◽  
Structural Engineers ◽  
Steel Trusses ◽  
Steel Roof

A steel truss is a preferred solution in large-span roof structures due to its good attributes such as lightweight, durability. However, designing steel trusses is a challenging task for engineers due to a large number of design variables. Recently, optimization-based design approaches have demonstrated the great potential to effectively support structural engineers in finding the optimal designs of truss structures. This paper aims to use the AdaBoost-DE algorithm for optimizing steel roof trusses. The AdaBoost-DE employed in this study is a hybrid algorithm in which the AdaBoost classification technique is used to enhance the performance of the Differential Evolution algorithm by skipping unnecessary fitness evaluations during the optimization process. An example of a duo-pitch steel roof truss with a span of 24 meters is carried out. The result shows that the AdaBoost-DE achieves the same optimal design as the original DE algorithm, but reduces the computational cost by approximately 36%.

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