Wind resistant design of buildings often needs to acquire wind spectra from wind tunnel tests. Using regression formulas to process and analyze experimental data of wind spectra usually is not very accurate. Therefore, one of the most important issue is how to use experimental wind load aerodynamic database more effectively. A wind pressure database for hemispherical dome roofs was collected. The emphases of the research were on the study of wind pressure spectra on the meridian with the change of curvature and height as well as the establishment of an Artificial Neural Network (ANN) prediction model. Random center selection method was used to write Radial Basis Function Neural Network (RBFNN) programs to train, validate and test the ANNs. The estimation models found not only accurate but also theoretically consistent. ANN Models were also compared with previous regression formula showing better accuracy and applicability.
關聯:
Journal of the Chinese Institute of Civil and Hydraulic Engineering 31(8), p.739-746