Optimum design method for simplified model of outrigger and ladder systems in tall buildings using genetic algorithm

Alhaddad, Wael; Halabi, Yahia; Meree, Hani; Yu, Zhixiang

doi:10.1016/j.istruc.2020.09.066

Cited by 14 publications

(9 citation statements)

References 55 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Commonly used chromosome encoding methods include binary encoding, character encoding, and floating-point number encoding. The specific encoding method to be used needs to be determined through the analysis of actual problems [ 24 ].…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Evaluation of Ideological and Political Education under Deep Learning Neural Network

Wang

2022

Computational Intelligence and Neuroscience

View full text Add to dashboard Cite

Under the background of the rapid development of the new generation of information technology, artificial neural networks (ANNs) have made some progress in the evaluation research of various courses in colleges and universities. However, there is little research on the application of ANNs in Ideological and Political Education (IPE) courses. Based on this, this work attempts to introduce the Backpropagation Neural Network (BPNN) into the evaluation system of IPE courses. Firstly, the structure and characteristics of the BPNN are given, and it is optimized by the genetic algorithm based on its characteristics. Secondly, the theoretical framework of IPE course evaluation is established, and the corresponding evaluation model is constructed using the optimized BPNN. Finally, a questionnaire survey is designed to analyze the current situation of IPE evaluation in colleges and universities, and a simulation experiment is set up to test the BPNN evaluation model before and after optimization. The results are as follows. First, there are mainly five evaluation methods for IPE courses in Chinese colleges and universities: 6/4, 3/7, 2/2/6, 5/5, and 3/3/4. Second, the training error value of the BPNN model is in the interval (−2.3, 2.2), and when the number of cycles is 552, the error is infinitely close to zero. Thirdly, the training error value of the optimized BPNN model is in the interval (−0.22, 1.2), and when the number of cycles is 775, the error is infinitely close to zero. Fourthly, the error between the output value of the optimized BPNN model and the expert score value is generally smaller than the error value before optimization. This work aims to provide a theoretical reference for the further application of neural network technology in the evaluation of IPE.

show abstract

Section: Methodsmentioning

confidence: 99%

“…e specific encoding method to be used needs to be determined through the analysis of actual problems [24].…”

Section: Basic Operation Of Gamentioning

confidence: 99%

Evaluation of Ideological and Political Education under Deep Learning Neural Network

Wang

2022

Computational Intelligence and Neuroscience

View full text Add to dashboard Cite

show abstract

“…Due to the very complex nature of plastic and nonlinear concrete, a small error is observed in the output. To examine all the above possible scenarios with five parameter in each of five cases, it is necessary to develop 5 5 = 3125 models in the Abaqus software. At this point, however, the design expert software reduced the required models to 50.…”

Section: Finite Element Model Validationmentioning

confidence: 99%

“…Structural safety is always the main concern that an engineer should take into account, while economic design should also be considered by relying on the optimization problem [4]. Several design variables can be considered in the formulation of the optimization problem [5,6]. The structural optimization problems can be divided into three open research areas: (1) optimization, (2) modeling and solving new structural engineering problems as optimization problems, and (3) analysis [7].…”

Section: Introductionmentioning

confidence: 99%

Optimization of through-bolt steel beam connection to CFST column reinforced with rib plates using RSM method and MCEO algorithm

Soumeh

Sani

2021

NMCE

View full text Add to dashboard Cite

Today, one of the most important engineering requirements is to ensure optimal design with best possible seismic performance of structures. To this end, the present paper aims to apply the optimization process for the design of the through-bolt steel beam connection to the concretefilled steel tube (CFST) column reinforced with rib plates. This study employs a multi-level cross-entropy optimizer (MCEO) algorithm along with response surface method (RSM) and finite element method (FEM) to establish the objective functions and constraints. The variables considered are the rib plate geometry and the steel and concrete strength parameters. In order to overcome problems, optimization is performed to increase the load-bearing capacity of the connection and to satisfy the constraints. Adopting this smart solution eliminates the need to connect finite elements for loop optimization and provides an explicit function for system performance. The results show that a very accurate analytical model can be developed to describe system performance using this process. This solution can optimize the performance of several systems that require a large amount of analysis and solve a wide range of structural optimization problems.

show abstract

“…Al Haddad et al (2020) investigated the location of outriggers in tall structures with the use of the genetic algorithm. They demonstrated that optimizing the position of outrigger arms would result in a considerable decrease in construction costs; however, it would lead to an increase in the design procedure time interval 8 . Salman et al (2020) investigated the structural response of high‐rise buildings through static and dynamic analyses and concluded that the outrigger braced system provides the most appropriate control on the structural behavior 9 .…”

Section: Introductionmentioning

confidence: 99%

Fragility assessment of an outrigger structure system based on energy method

Goodarzi

Moradi

Jalali

et al. 2023

Structural Design Tall Build

View full text Add to dashboard Cite

Fragility curves development in structures has always been a focus of research interest among structural and earthquake engineers for which the maximum story drift is usually considered as the engineering demand parameter (EDP) known as the conventional approach. This paper aims at calculating the fragility curves of a tall building with outrigger braced system by considering the plastic strain energy as the EDP and compare it with the conventional approach. In addition, the effect of optimizing the position of outriggers on the exceedance probability of the structure under near-and far-fault seismic loadings is investigated in this paper. Fragility curves of this structure in four performance levels including immediate occupancy (IO), life safety (LS), collapse prevention (CP), and instability is extracted based on the conventional method.The fragility curves for the aforementioned performance levels are also extracted based on the plastic strain energy and compared with the conventional approach.The results have demonstrated that optimizing the location of the bracing system would lower the exceedance probability of the structure. Moreover, the exceedance probability of the investigated building with outrigger braced system under far-fault records in various levels is more than that of near-fault records. It is also concluded that the conventional approach would lead to more conservative results compared with the energy approach.

show abstract

Optimum design method for simplified model of outrigger and ladder systems in tall buildings using genetic algorithm

Cited by 14 publications

References 55 publications

Evaluation of Ideological and Political Education under Deep Learning Neural Network

Evaluation of Ideological and Political Education under Deep Learning Neural Network

Optimization of through-bolt steel beam connection to CFST column reinforced with rib plates using RSM method and MCEO algorithm

Fragility assessment of an outrigger structure system based on energy method

Contact Info

Product

Resources

About