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Generalization Capabilities of Feedforward Neural Networks for Pattern Recognition
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作者 黄德双 《Journal of Beijing Institute of Technology》 EI CAS 1996年第2期192+184-192,共10页
This paper studies the generalization capability of feedforward neural networks (FNN).The mechanism of FNNs for classification is investigated from the geometric and probabilistic viewpoints. It is pointed out that th... This paper studies the generalization capability of feedforward neural networks (FNN).The mechanism of FNNs for classification is investigated from the geometric and probabilistic viewpoints. It is pointed out that the outputs of the output layer in the FNNs for classification correspond to the estimates of posteriori probability of the input pattern samples with desired outputs 1 or 0. The theorem for the generalized kernel function in the radial basis function networks (RBFN) is given. For an 2-layer perceptron network (2-LPN). an idea of using extended samples to improve generalization capability is proposed. Finally. the experimental results of radar target classification are given to verify the generaliztion capability of the RBFNs. 展开更多
关键词 feedforward neural networks radial basis function networks multilayer perceptronnetworks generalization capability radar target classification
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A rain-type adaptive optical flow method and its application in tropical cyclone rainfall nowcasting 被引量:3
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作者 Jiakai ZHU Jianhua DAI 《Frontiers of Earth Science》 SCIE CSCD 2022年第2期248-264,共17页
A rain-type adaptive pyramid Kanade-Lucas-Tomasi(A-PKLT)optical flow method for radar echo extrapolation is proposed.This method introduces a rain-type classification algorithm that can classify radar echoes into six ... A rain-type adaptive pyramid Kanade-Lucas-Tomasi(A-PKLT)optical flow method for radar echo extrapolation is proposed.This method introduces a rain-type classification algorithm that can classify radar echoes into six types:convective,stratiform,surrounding convective,isolated convective core,isolated convective fringe,and weak echoes.Then,new schemes are designed to optimize specific parameters of the PKLT optical flow based on the rain type of the echo.At the same time,the gradients of radar reflectivity in the fringe positions corresponding to all types of rain echoes are increased.As a result,corner points that are characteristic points used for PKLT optical flow tracking in the surrounding area will be increased.Therefore,more motion vectors are purposefully obtained in the whole radar echo area.This helps to describe the motion characteristics of the precipitation more precisely.Then,the motion vectors corresponding to each type of rain echo are merged,and a denser motion vector field is generated by an interpolation algorithm on the basis of merged motion vectors.Finally,the dense motion vectors are used to extrapolate rain echoes into 0-60-min nowcasts by a semi-Lagrangian scheme.Compared with other nowcasting methods for four landfalling typhoons in or near Shanghai,the new optical flow method is found to be more accurate than the traditional cross-correlation and optical flow methods,particularly showing a clear improvement in the nowcasting of convective echoes on the spiral rainbands of typhoons. 展开更多
关键词 optical flow method radar echo classification ADAPTIVE TYPHOON NOWCASTING
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