| Diagnosis Model Based Neutral-network in Galactophore Cancer Cell Identification |
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| 引用本文： | LIU Qiong sun,HE Li qing. Diagnosis Model Based Neutral-network in Galactophore Cancer Cell Identification[J]. 保鲜与加工, 2003, 0(4): 70-72 |
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| 作者姓名： | LIU Qiong sun HE Li qing |
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| 摘 要： | To the classified problem of the Galactophore Cancer Cell Identification, the paper researched the classified mechanism and optimized parameter for more-layer radial basis function (RBF) network, adopted the method of gradient descent with momentum and adaptive learned backpropagation, constructed the two-model of the Galactophore Cancer Cell Identification based on BP Neural-Network and RBF Network. Classified principle based on RBF Neural network was also discussed, and the method for data processing was studied. RBF network has more advantage, such as fault tolerance, nonlinear mapping, etc.. Experiment results show that, on the model based RBF Neural Network, performance is steady, training time is short and classified results are good.
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| 关 键 词： | neural-network pattern classification diagnosis identification |
| 修稿时间： | 2002-11-14 |
Diagnosis Model Based Neutral-network in Galactophore Cancer Cell Identification |
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| LIU Qiong sun,HE Li qing. Diagnosis Model Based Neutral-network in Galactophore Cancer Cell Identification[J]. Storage & Process, 2003, 0(4): 70-72 |
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| Authors: | LIU Qiong sun HE Li qing |
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| Abstract: | To the classified problem of the Galactophore Cancer Cell Identification, the paper researched the classified mechanism and optimized parameter for more-layer radial basis function (RBF) network, adopted the method of gradient descent with momentum and adaptive learned backpropagation, constructed the two-model of the Galactophore Cancer Cell Identification based on BP Neural-Network and RBF Network. Classified principle based on RBF Neural network was also discussed, and the method for data processing was studied. RBF network has more advantage, such as fault tolerance, nonlinear mapping, etc.. Experiment results show that, on the model based RBF Neural Network, performance is steady, training time is short and classified results are good. |
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| Keywords: | neural-network pattern classification diagnosis identification |
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