融合双重BP神经网络组合模型的Python解析计算机网络上传数据算法

Python Analytical Computer Network Uploading Data Algorithm Which Combines A Combination Model of Dual BP Neural Network

针对手工提取网络上传数据过程烦琐、工作量大的问题,提出一种融合双重BP神经网络组合模型(A combination model of dual BP neural network,CMDBPNN)的Python解析计算机网络上传数据算法.该算法对BP神经网络组合模型的空间实施网络化处理,且对于网络单元中的信息也可以借助相似的方法来进行记录,依据优化之后的金字塔时间结构对其中潜藏的网格单元来实施有效的存储,以实现Python解析计算机网络上传的数据算法.最后,利用真实数据集与仿真数据集进行实验.结果表明:该算法具有良好的适用性和有效性.

In view of the cumbersome and heavy workload of the manual extraction of data from the network,a kind of Python analytical computer network uploading data algorithm which combines a combination model of dual BP neural network（ CMDBPNN） is proposed. The algorithm is used to deal with the space of a combination model of dual BP neural network,and the information in the network unit can also be recorded with the aid of a similar method. According to the optimized Pyramid time structure,the latent grid unit is stored effectively to realize the data algorithm uploaded by the Python computer network. Finally,the experiments are carried out by using the real data sets and the simulation data sets,and the results show that the algorithm has good applicability and effectiveness.