As a new entertainment and social way, online games now have a huge and increasing user group, so it is of great significance to identify the data stream of online games. Using the excellent nonlinear fitting ability of BP neural network and the advantages of global search of genetic algorithm, the initial weights and thresholds of BP neural network are optimized, and the BP neural network model optimized by genetic algorithm is established. The muti-dimensional input information is proposed to identify online game data streams. Through the experimental simulation, it shows that the selected muti-dimensional information and the established model can be well applied to online game stream recognition.

ABSTRACT
1. Introduction
2. BP neural network optimized bygenetic algorithm
    2.1 Basic principles of genetic algorithm
    2.2 genetic algorithm optimizes BP neuralnetwork algorithm model
3. Network game data stream recognitionmodel
    3.1 data sources
    3.2 data quantification
    3.3 Identification model
4. Experimental analysis
    4.1 parameter setting
6. Conclusions
References

• Daniel James(Association of Scientists, Developers and Faculties 483, Green Lanes, Enfield, London N13 4BS, England, United Kingdom) Corresponding author