N. B. Ghazali1, F. C. Seman1,*, K. Isa1, K. N. Ramli1, Z. Z. Abidin1, S. M. Mustam1, M. A. Haek2, A. N. Z. Abidin2, A. Asrokin2
CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5427-5440, 2022, DOI:10.32604/cmc.2022.023211
Abstract Applying the fault diagnosis techniques to twisted pair copper cable is beneficial to improve the stability and reliability of internet access in Digital Subscriber Line (DSL) Access Network System. The network performance depends on the occurrence of cable fault along the copper cable. Currently, most of the telecommunication providers monitor the network performance degradation hence troubleshoot the present of the fault by using commercial test gear on-site, which may be resolved using data analytics and machine learning algorithm. This paper presents a fault diagnosis method for twisted pair cable fault detection based on knowledge-based and data-driven machine learning methods. The… More >
Login
Register
