Artificial intelligence (AI) is an extensive scientific discipline which enables computer systems to solve problems by emulating complex biological processes such as learning, reasoning and self-correction. This paper presents a comprehensive review of the application of AI techniques for improving performance of optical communication systems and networks. The use of AI-based techniques is first studied in applications related to optical transmission, ranging from the characterization and operation of network components to performance monitoring, mitigation of nonlinearities, and quality of transmission estimation. Then, applications related to optical network control and management are also reviewed, including topics like optical network planning and operation in both transport and access networks. Finally, the paper also presents a summary of opportunities and challenges in optical networking where AI is expected to play a key role in the near future.

No abstract

For reliable operation and control of smart grid, estimating the correct states is of utmost importance to the system operator. With recent incorporation of information technology and Advanced Metering Infrastructure (AMI), the futuristic grid is more prone to cyber-threats. The False Data Injection (FDI) attack is one of the most thoroughly researched cyberattacks. Intelligently crafted, it can cause false estimation of states, which further seriously affects the entire power system operation. In this paper, we propose Joint Transformation based scheme to detect FDI attacks in real time. The proposed method is built on the dynamics of measurement variations. Kullback-Leibler Distance (KLD) is used to find out the difference between probability distributions obtained from measurement variations. The proposed method is tested using IEEE 14 bus system considering attack on different state variables. The results shows that the proposed scheme detects FDI attacks with high detection probability.

No abstract

No abstract