What is it about?
Nowadays, it has become a key point in data competition to use algorithms and neural networks to predict different expected indicators. This paper improves the data processing efficiency and the timeliness and stability of the system prediction by improving the traditional recurrent neural network.
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Why is it important?
Compared with the traditional prediction system, this prediction system has some advantages in serial modeling and has the function of long-term memory. At the same time, the problems of gradient disappearing and gradient explosion in long sequence training are solved. The neuronal algorithm can accelerate the convergence of the prediction model and ensure the stability of the change trend of the evaluation parameters.
Perspectives
I had a lot of fun writing this article, and I want more people to benefit from it.
子萁 高
Read the Original
This page is a summary of: Establishment and Evaluation of Measurement and Control System Model Based on Data Analysis Optimization, November 2022, ACM (Association for Computing Machinery),
DOI: 10.1145/3582935.3582991.
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