Online study method of RBF neural network and its application in the dam displacement monitoring
2006
Wang Dewen | Li Zhilu | Lu Ruizhang
Chino. 针对目前RBF神经网络训练算法存在的问题，提出了一种模拟人类学习方式的自动调整隐层节点数的在线训练方法，对其理论依据进行了分析，并用实例对其进行了验证。结果表明，此种学习方法速度快、拟合精度高、新旧知识均可记忆，克服了以往算法的不足，具有很大的实用性。
Mostrar más [+] Menos [-]Inglés. Aiming at the present problem in RBF neural network, an on-line training algorithm is presented, which can simulate the study of human and modify the nodes automatically. The theory on which this algorithm is based has been discussed. Results show that the algorithm can study fast and memorize both new and old knowledge with high simulating precision. So the algorithm can overcome the shortcomings of other existing algorithms and has great practicability.
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Este registro bibliográfico ha sido proporcionado por Institute of Agricultural Information, Chinese Academy of Agricultural Sciences