Application of artificial intelligence technique in optimization and prediction of the stability of the walls against wind loads in building design

Hu, Dongyan; Sun, Hongquan; Mehrabi, Peyman; Ali, Yasser A.; Al-Razgan, Muna

doi:10.1080/15376494.2023.2206208

Cited by 47 publications

(5 citation statements)

References 62 publications

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“…The correlation coefficients (r) suggest a positive relationship between predicted and actual values, indicating that the algorithm is capturing relevant patterns in the data. This smooth performance of the APG algorithm thoroughly confirms that the elasticity of the fibers has a significant role in the flexural behavior of FRC [33][34][35].…”

Section: Apgsupporting

confidence: 64%

“…The typical function of the second layer is described in Equation (3) while a node Based on the theory of ANFIS network abilities, a single node without any identified weight moves in a system of adjusted layers to another until the final node finds the correct answer [34,59,60]. The aforementioned cycle has been demonstrated in Figure 8; five layers are typically performed in succession and have a membership function effect on the final layer.…”

Section: Artificial Intelligence Algorithms 221 Anfis Architecturementioning

confidence: 99%

“…The aforementioned cycle has been demonstrated in Figure 8; five layers are typically performed in succession and have a membership function effect on the final layer. Just in the case of conservation, the authors assume that the ANFIS has two described inputs such as V 1 and V 2 , and one output as f. According to the Takagi, Sugeno and Kang theory [34], two rules are described below:…”

Section: Artificial Intelligence Algorithms 221 Anfis Architecturementioning

confidence: 99%

“…For the identification of fiber properties, using a single value of mechanical strength at the first crack moment is not conservative. Likewise, based on the first crack strength, any conclusion could be misleading [34].…”

Section: Introductionmentioning

confidence: 99%

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Comparative Study in Design of Fiber-Reinforced Concrete at Elevated Temperatures by Numerical Evaluation through Developed Hybrid Metaheuristic Algorithms

et al. 2023

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Fibrous concrete has good properties such as high ductility, high strength, suitable energy absorption and cracking resistance, which can be useful in many applications. This type of concrete is one of the best materials used in the construction of impact-resistant masonries, such as burial masonry structures, and explosive masonry warehouses. In this study, an artificial intelligence assessment based on the experimental test data from a laboratory has been performed on the fibrous concrete to evaluate the behavior of the samples at elevated temperatures and determine the most governing parameter on the mechanical properties of the fibrous concrete at elevated temperatures. For the first time, a hybrid intelligence algorithm has been developed based on the neural network structure using both genetic and swarm optimization algorithms. The ANFIS-PSO-GA (APG) algorithm was trained with experimental data and evaluated the flexural load and deflection of the samples. In order to detect the most prominent feature in the fire resistance of the fibrous concrete, five different subdatasets were designed. The results of the APG algorithm have been challenged with the ANFIS-PSO algorithm, which is a well-known hybrid numerical evaluation algorithm. As per the results, the newly designed APG algorithm has been successfully performed on both deflection and flexural prediction phases. Based on the numerical achievements, fiber features such as the fiber content and fiber mechanical properties are governing factors on the fibrous concrete resistance at elevated temperatures.

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Section: Apgsupporting

confidence: 64%

Section: Artificial Intelligence Algorithms 221 Anfis Architecturementioning

confidence: 99%

Section: Artificial Intelligence Algorithms 221 Anfis Architecturementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Comparative Study in Design of Fiber-Reinforced Concrete at Elevated Temperatures by Numerical Evaluation through Developed Hybrid Metaheuristic Algorithms

et al. 2023

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“…This enhancement can lead to better performance and increased durability of concrete when subjected to a variety of load conditions, including seismic disturbances [9][10][11]. Therefore, it is crucial to furnish policymakers with enhanced understanding to guide their decision making towards sustainable development and associated infrastructures [12][13][14]. Concrete's role in sustainable development is deeply intertwined with the use of cement, which forms the foundation of the infrastructure that concrete strengthens and supports.…”

Section: Introductionmentioning

confidence: 99%

Improving the Mechanical Properties of Concrete Mixtures by Shape Memory Alloy Fibers and Silica Fume

Xie,

Far,

Mortazavi

et al. 2024

Buildings

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Concrete, as one of the most widely applied materials in buildings, has high environmental impacts. Researchers are continually seeking solutions to mitigate these environmental issues while enhancing the mechanical strength and durability of concrete. However, there is a lack of studies on the effect of combining silica fume (SF) as pozzolanic materials and shape memory alloy (SMA) fibers on the mechanical properties of concrete. Moreover, there is very limited research on the influence of these materials on concrete mixtures after primary failure cracks using the secondary compressive strength test. In this research, 0.1, 0.2, and 0.3% SMA and 5, 7.5, and 10% SF were applied and then subjected to compressive strength, splitting tensile strength, flexural strength, secondary compressive strength, and ultrasonic pulse velocity tests. According to the results, 10% SF is more economical, which increases the compressive, splitting tensile, and flexural strength by 14%, 7%, and 10%, respectively. Also, using 0.3% SMA improves the compressive, splitting tensile, and flexural strength by 2%, 5%, and 8%, respectively. Furthermore, SMA has the ability to reduce the secondary compressive strength compared to other samples, indicating the quality of this material in controlling stress after cracking. Finally, it was indicated that the combined use of these two materials increases the strength parameters.

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Comprehensive review of AI and ML tools for earthquake damage assessment and retrofitting strategies

Bhadauria

2024

Earth Sci Inform

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Application of artificial intelligence technique in optimization and prediction of the stability of the walls against wind loads in building design

Cited by 47 publications

References 62 publications

Comparative Study in Design of Fiber-Reinforced Concrete at Elevated Temperatures by Numerical Evaluation through Developed Hybrid Metaheuristic Algorithms

Comparative Study in Design of Fiber-Reinforced Concrete at Elevated Temperatures by Numerical Evaluation through Developed Hybrid Metaheuristic Algorithms

Improving the Mechanical Properties of Concrete Mixtures by Shape Memory Alloy Fibers and Silica Fume

Comprehensive review of AI and ML tools for earthquake damage assessment and retrofitting strategies

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