Design and Research of Data Routing Simulation Software Based on Neural Network Algorithm

Wireless sensor network (WSN) deploys sensor nodes in the monitoring area in the form of a certain topology or self-organizing network. The nodes monitor the target object in real time and send the collected data information to the base station in a direct or indirect way. The received data information is comprehensively processed by the base station to obtain more accurate target information, and the user terminal makes relevant decisions based on this information. In this paper, a design and simulation scheme of WSN routing protocol based on neural network algorithm is proposed. The influence of sample data on weights is obtained by using the reliability allocation strategy, and the initial weights closer to the actual weights are calculated. The results show that the convergence speed of WSN routing protocol network based on neural network algorithm is accelerated, the output error is reduced, the accuracy of information collection is improved, and the quality of data fusion is improved. Different application scenarios have different requirements for the network, such as the number of sensor nodes, the size of the monitoring area, different service quality requirements of users, etc. The network must have an effective mechanism to adapt to these scalability.