A new method for prediction of wing aerodynamic performance in rain condition was presented.Three-and four-layer artificial neural networks based on improved algorithm for error Back Propagation(BP)network were respec...A new method for prediction of wing aerodynamic performance in rain condition was presented.Three-and four-layer artificial neural networks based on improved algorithm for error Back Propagation(BP)network were respectively built.Detailed approaches to determine the optical parameters for network model were introduced and the specific steps for applying BP network model to predict wing aerodynamic performance in rain were given.On this basis,the established optimal three-and four-layer BP network model was used for this prediction.Results indicate that both of the network models are appropriate for predicting wing aerodynamic performance in rain.The sum of square error level produced by two models is less than 0.2%,and the prediction accuracy by four-layer network model is higher than that of three-layer network.展开更多
The article is dealing with different classification methods applied for urban aerial photos having visible and infrared channels. An accuracy assessment was carried out to compare the results gained from different cl...The article is dealing with different classification methods applied for urban aerial photos having visible and infrared channels. An accuracy assessment was carried out to compare the results gained from different classification methods.展开更多
文摘A new method for prediction of wing aerodynamic performance in rain condition was presented.Three-and four-layer artificial neural networks based on improved algorithm for error Back Propagation(BP)network were respectively built.Detailed approaches to determine the optical parameters for network model were introduced and the specific steps for applying BP network model to predict wing aerodynamic performance in rain were given.On this basis,the established optimal three-and four-layer BP network model was used for this prediction.Results indicate that both of the network models are appropriate for predicting wing aerodynamic performance in rain.The sum of square error level produced by two models is less than 0.2%,and the prediction accuracy by four-layer network model is higher than that of three-layer network.
基金The research was carried out thanks to the image data offered by the Obuda University,Alba Regia Technical Faculty in the frame of the project No.TÉT_12_CN-1-2012-0026The research was supported also by the following projects:China National Natural Science Foundation with Project No.41471310 Study on Urban Green Space Index Retrieval Model based on Airborne LiDAR+1 种基金Study on the urban imperious surface monitoring technique with hyper-spectral remote sensing data,2012B091100219,Guang dong Province-Chinese Academy of Sciences Industry-Education-Research joint funding projectIntegrated geo-spatial information technology and its application to resource and environmental management towards the GEOSS(EU FP7 PIRSES-GA-2009-247608).
文摘The article is dealing with different classification methods applied for urban aerial photos having visible and infrared channels. An accuracy assessment was carried out to compare the results gained from different classification methods.
