with the popularization and development of computer and network information technology, network information and the Internet communication of all kinds of information is distributed in all areas of the network, which makes the multi-tier distribution is the development of the system from the host system for the server application, multilayer distributed system has gradually become the mainstream of computer and network information technology. In order to solve the problems in the multi-layer distributed system based on neural network adaptation, this paper first introduces the basic structure of the multi-layer distributed system and the steps of the approximation function of RBF neural network adaptation, and then briefly describes the development tools and software Settings of the multi-layer distributed system based on neural network adaptation. Finally, the architecture of neural network adaptive multi-layer distributed system is designed and discussed. Finally, the application of neural network adaptive and other algorithms in multi-layer distributed system is compared with experimental data. The experimental results show that the multilayer distributed system based on neural network adaptive in the application of noise signal to the noise cancellation effect of sawtooth wave and output letter manic ratio up to 26.23, 26.02 in the rectangular wave, 24.79 in the sine wave, so it can be seen that the multilayer distributed system based on neural network adaptive of superiority.

Ernesten Foosh. Adaptive Multi-layer Distributed System Based on Neural Network. Distributed Processing System (2022), Vol. 3, Issue 3: 45-52. https://doi.org/10.38007/DPS.2022.030306.

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