Abstract ： To solve the defects of traditional fault diagnosis neural network, such as long training time, complex structure and single-valued input, a fault diagnosis system for civil aircraft based on rough-neural network was proposed. Rough set theory was applied to the front-end neural network to reduce the data of civil aircraft fault sample so as to remove the disturbance of redundant attributes, and overcome the impaction of unrelated data that imposed on the performance of network learning, simplify network structure.
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By making use of the scheme after improving, it can simplify network structure, accelerate operation, and shorten the training time.
利用改进后的方案实现语音识别、网络结构简化、运算速度加快、训练时间缩短。
This model was applied to. reduce factors of weather, withdraw essential ingredient as the input of the network, and simplify network structure.
该模型利用粗糙集理论约简气象影响因素，提取关键因素作为网络的输入，简化了网络结构。
Based on the wavelet neural network, this paper proposes a new network named varying scales wavelet neural network to reduce wavelet-neuron Numbers and simplify network structure.
基于小波神经网络，文中提出了可变尺度小波神经网络，可减少隐层神经元数目，精简网络结构。
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