Research on Fault Warning Technology of Optical Network Based on Recurrent Neural Network

With the rapid development of cyber information system construction, optical networks, as a crucial component of the cyber information infrastructure, carry an increasing amount of data information and directly determine the performance of the network information system. The occurrence of faults in optical networks can severely impact various information transmissions; hence, fault warning and analysis are essential to ensure the stable and reliable operation of optical networks. Traditional fault warning and analysis of optical networks mainly rely on expert experience and network management system alarms, which have limitations such as long training cycles for backbone personnel, poor fault tolerance of network management systems, and long cycles for knowledge base construction. These limitations make it difficult to provide early warnings before faults occur in optical transmission networks, and the implementation of intelligent operation and maintenance of optical networks is challenging. Therefore, warning of optical network performance helps to accurately detect hidden dangers and determine fault causes before faults occur in optical transmission networks, and to prepare spare boards, fiber cores, and backbone forces in advance, minimizing repair time and achieving "zero" fault perception for users. This paper proposes an optical network fault warning model based on recurrent neural networks to achieve high-accuracy and intelligent response for optical network fault warnings.