Risk Assessment of Optical Fiber Communication Network Based on BP Network Optimized By Genetic Algorithm
Huale Zhang, Xiaowei Wang, Rui Cheng, Lanlan Zhang, Huijie Chen, Jingxue Liu · 2023
With the continuous progress of social science and technology, the communication industry has developed rapidly. The state has also increased the development and application of optical fiber communication systems. Optical fiber communication technology is applied in various fields of modern communication, and it has become a new symbol of modern communication technology development. As far as the current situation is concerned, optical fiber communication has been widely used in many fields of society. The main reason is that optical fiber communication has the characteristics of fast transmission speed and low energy consumption, which has been recognized by many people. Genetic algorithm is a search algorithm based on natural genetic and natural selection mechanism. It applies the important mechanism of natural biological system to the design of artificial system. The advantages of simplicity, high robustness and global search make genetic algorithm widely used in system control, numerical optimization and other fields. In view of the shortcomings of BP algorithm, such as slow convergence speed and easy to fall into local optimum, genetic algorithm is used to learn the weights of BP network. In order to ensure the safety of optical fiber communication network and improve the risk assessment accuracy of optical fiber communication network, this paper proposes a risk assessment model of optical fiber communication network based on intelligent classification algorithm. The risk evaluation index of optical fiber communication network is constructed and preprocessed, then the correlation between the evaluation indexes is calculated, the optimal evaluation index set is selected, and the redundant indexes are removed. Finally, the intelligent classification algorithm is used to establish the risk evaluation model of optical fiber communication network and realize the estimation of the risk level.