基于人工神经网络的不良信息实时监测原型系统

Real Time Monitoring Prototype System for Bad Information Based on Artificial Neural Networks

根据不良信息过滤的目标及特点,设计了一个基于神经网络的不良信息实时监测原型系统,并用软件实现。在系统的决策支持模块中,采用了一个新的神经网络算法,大大提高了系统决策的准确性,同时该系统也很好地处理了包捕获及处理速度、经济可行性等相关问题,具有一定的应用价值。

Aiming at the goal and tenet of filtrating bad information, a real time monitoring prototype system for bad information based on the artificial neural networks is brought forward and is implemented by soft. Owing to the application of a new algorithm of artificial neural network in the decision making module, the veracity of decision-making in the system is greatly improved. At the same time, some correlative problems, such as the speed of capture, transaction of the packages and the feasibility in economy, are dealt with in the system.