遗传算法优化BP神经网络的网络游戏流识别

Recognition for Online Games Stream of Optimized BP Neural Network Based on Genetic Algorithm

网络游戏作为一种新兴的娱乐社交方式,现已拥有着庞大的用户群体,且不断增加,因此对网络游戏数据流进行识别有十分重要的意义。利用BP神经网络优秀的非线性拟合能力,结合遗传算法全局搜索的优点,优化BP神经网络的初始权值和阈值,建立遗传算法优化的BP神经网络模型,并提出利用多维度输入信息对网络游戏数据流进行识别。通过实验仿真,说明选取的多维信息和建立的模型能够很好地应用于网络游戏流识别。

As a new way of entertainment and social networking,online games have a huge user group and are increasing.Therefore,it is of great significance to identify the data stream of online games.Based on the excellent non-linear 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,the BP neural network model optimized by genetic algorithm is established,and the multi-dimensional input informa⁃tion is used to identify the online game data stream.Experiments show that the selected multi-dimensional information and the estab⁃lished model can be well applied to online game stream identification.