Abstract

In order to solve the problem that the data processing frequency of the traditional centralized data processing system is low, which leads to the poor feedback effect of massive data, this paper proposes a computer data information processing system based on neural network algorithm. Based on the original system hardware, the system replaces the data processor and increases the total number of the processor, so as to realize the distributed synchronous processing of massive data. In the aspect of software design, the interaction between system units and modules is formed through the protocol to improve the data communication mode of the system; Calculate the Euclidean distance and set the distributed processing mode of the system; According to the definition of cloud computing, the classification function is used to determine the constraints, establish the processing frequency equation, and realize the rapid processing of massive data. The experimental results show that the processing frequency of the system designed in this paper is more than 50% higher than that of the traditional system, which solves the problem of low processing frequency caused by weak analysis ability and slow response speed in the traditional system. Conclusion: compared with the traditional system, the system designed in this paper has faster processing frequency for massive data and better feedback effect to users.

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