All Outputs (4)

Utilization of demand side management for stability improvement in renewable energy resources in United Kingdom. (2024)
Presentation / Conference Contribution
SUNDAS, R., ATALOR, D.O., BAIG, N.A. and YAHYA, H. 2024. Utilization of demand side management for stability improvement in renewable energy resources in United Kingdom. In Proceedings of the 2024 Future technologies conference (FTC 2024), 14-15 November 2024, London, UK. Lecture notes in networks and systems, 1154. Cham: Springer [online], 1, pages 558-571. Available from: https://doi.org/10.1007/978-3-031-73110-5_37

This research deals with the Particle Swarm Optimization (PSO) algorithm for a meagre load shifting in demand side management focusing on scheduling the residential, commercial, and industrial load in United Kingdom. Irregular and unscheduled load co... Read More about Utilization of demand side management for stability improvement in renewable energy resources in United Kingdom..

Power transformer health index and life span assessment: a comprehensive review of conventional and machine learning based approaches. (2024)
Journal Article
ZAHRA, S.T., IMDAD, S.K., KHAN, S., KHALID, S. and BAIG, N.A. 2025. Power transformer health index and life span assessment: a comprehensive review of conventional and machine learning based approaches. Engineering applications of artificial intelligence [online], 139(A), article number 109474. Available from: https://doi.org/10.1016/j.engappai.2024.109474

Power transformers play a critical role within the electrical power system, making their health assessment and the prediction of their remaining lifespan paramount for the purpose of ensuring efficient operation and facilitating effective maintenance... Read More about Power transformer health index and life span assessment: a comprehensive review of conventional and machine learning based approaches..

Next-gen solutions: deep learning-enhanced design of joint cognitive radar and communication systems for noisy channel environments. (2024)
Journal Article
MUNIR, M.F., BASIT, A., KHAN, W., SALEEM, A., KHALIQ, A. and BAIG, N.A. 2024. Next-gen solutions: deep learning-enhanced design of joint cognitive radar and communication systems for noisy channel environments. Computers and electrical engineering [online], 120(Part A), article number 109663. Available from: https://doi.org/10.1016/j.compeleceng.2024.109663

In recent years, the dual-function radar and communication (DFRC) paradigm has emerged as a focal point in addressing spectrum congestion challenges. However, prevailing research heavily relies on computationally complex likelihood-based approaches f... Read More about Next-gen solutions: deep learning-enhanced design of joint cognitive radar and communication systems for noisy channel environments..

Cognitive dual coprime frequency diverse array MIMO radar network for target discrimination and main-lobe interference mitigation. (2024)
Journal Article
KHAN, U.H., BASIT, A., KHAN, W., JADOON, M.A.K. and BAIG, N.A. 2024. Cognitive dual coprime frequency diverse array MIMO radar network for target discrimination and main-lobe interference mitigation. IET radar, sonar and navigation [online], 18(9), pages 1584-1597. Available from: https://doi.org/10.1049/rsn2.12595

The authors propose a novel dual coprime frequency diverse array (FDA) multiple input multiple output (DCFDA-MIMO) radar network design, empowered by cognitive capabilities, aimed at target discrimination and mitigation of interference present in the... Read More about Cognitive dual coprime frequency diverse array MIMO radar network for target discrimination and main-lobe interference mitigation..