Optimized Ga-Bp Neural Network Based Video Streaming In Wireless Technology For Online Teaching
Online teaching and education programs are most needed and directly insist us to adapt during this pandemic situation and increasing rapidly. Faculty need to be competent in their role and possess the skills necessary to positively impact student outcomes. As a novel online teaching network expertise, streaming media expertise can realize flexible and efficient two-way communication between teachers and students, simulate virtual face-to-face teaching environment, and yield enough emotional quality for both sides in the corresponding time and space. In view of the poor communication quality and flexibility of current streaming media technology, this paper will build a selective streaming media online teaching architecture based on animation media service platform. The system innovatively uses DXSDK filtering technology to realize real-time audio acquisition and filtering processing and solves the communication quality problem of streaming media online teaching. Aiming at the flexibility of streaming media online teaching, the system adds online auxiliary teaching function, which can realize online text communication, file information management, and learning tracking interaction between teaching and learning. From this research, experimental results, the stability and flexibility of the system are greatly improved within a certain range of users, which has obvious practical value. It has high stability and application value.