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- W4379419257 abstract "The world is advancing towards automation that provides timely solutions to real-time problems. Depending on varied customer demands, network management would be complex and diverse with advanced technologies, and it is hard for IT staff to analyze the reports manually, which may even include manual errors affecting the system. Thus, ML and AI can be utilized to train on numerous sources of data from multiple platforms, which on consolidation give speedy auto-diagnoses of problems in network management. In this chapter, the benefits of ML and AI are studied to efficiently handle big data and automate troubleshooting with personalized responses. The role of new technologies in the areas of various time-sensitive problems of network management are explored including congestion regulation, capacity designing, and security surveillance. ML and AI can also enhance the security of the system, and the challenges of using these new technologies are also discussed, hence paving the way to efficiently use ML and AI in the management of networks and providing directions for contributing to future research." @default.
- W4379419257 created "2023-06-06" @default.
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- W4379419257 date "2023-06-16" @default.
- W4379419257 modified "2023-09-26" @default.
- W4379419257 title "Artificial Intelligence and Machine Learning for Network Management" @default.
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- W4379419257 doi "https://doi.org/10.4018/978-1-6684-7348-1.ch001" @default.
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