Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Advances in Engineering Software
Hybrid high order neural networks
Applied Soft Computing
ICNC '09 Proceedings of the 2009 Fifth International Conference on Natural Computation - Volume 04
Using weighted genetic programming to program squat wall strengths and tune associated formulas
Engineering Applications of Artificial Intelligence
Aseismic ability estimation of school building using predictive data mining models
Expert Systems with Applications: An International Journal
Advances in Engineering Software
Predicting high-strength concrete parameters using weighted genetic programming
Engineering with Computers
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In general, the aseismic ability of buildings is analyzed using nonlinear models. To obtain aseismic abilities of buildings, numerical models are constructed based on the structural configuration and material properties of buildings, and their stress responses and behaviors are simulated. This method is complex, time-consuming, and should only be conducted by professionals. In the past, soft computing techniques have been applied in the construction field to predict the particular stress responses and behaviors; however, only a few studies have been made to predict specific properties of entire buildings. In this study, a weighted genetic programming system is developed to construct the relation models between the aseismic capacity of school buildings, and their basic design parameters. This is based on information from the database of school buildings, as well as information regarding the aseismic capacity of school buildings analyzed using complete nonlinear methods. This system can be further applied to predict the aseismic capacity of the school buildings.