Outputs (5)

An analytical framework for high-speed hardware particle swarm optimization (2019)
Journal Article
Damaj, I., Elshafei, M., El-Abd, M., & Aydin, M. E. (2020). An analytical framework for high-speed hardware particle swarm optimization. Microprocessors and Microsystems, 72, 102949. https://doi.org/10.1016/j.micpro.2019.102949

Engineering optimization techniques are computationally intensive and can challenge implementations on tightly-constrained embedded systems. Particle Swarm Optimization (PSO) is a well-known bio-inspired algorithm that is adopted in various applicati... Read More about An analytical framework for high-speed hardware particle swarm optimization.

Threats on the horizon: Understanding security threats in the era of cyber-physical systems (2019)
Journal Article
Walker-Roberts, S., Hammoudeh, M., Aldabbas, O., Aydin, M., & Dehghantanha, A. (2020). Threats on the horizon: Understanding security threats in the era of cyber-physical systems. Journal of Supercomputing, https://doi.org/10.1007/s11227-019-03028-9

Disruptive innovations of the last few decades, such as smart cities and Industry 4.0, were made possible by higher integration of physical and digital elements. In today's pervasive cyber-physical systems, connecting more devices introduces new vuln... Read More about Threats on the horizon: Understanding security threats in the era of cyber-physical systems.

A honeybees-inspired heuristic algorithm for numerical optimisation (2019)
Journal Article
Dugenci, M., & Aydin, M. E. (2020). A honeybees-inspired heuristic algorithm for numerical optimisation. Neural Computing and Applications, 32, 12311–12325. https://doi.org/10.1007/s00521-019-04533-x

© 2019, The Author(s). Swarm intelligence is all about developing collective behaviours to solve complex, ill-structured and large-scale problems. Efficiency in collective behaviours depends on how to harmonise the individual contributors so that a c... Read More about A honeybees-inspired heuristic algorithm for numerical optimisation.

A comparison of reinforcement learning algorithms in fairness-oriented OFDMA schedulers (2019)
Journal Article
Comşa, I., Zhang, S., Aydin, M., Kuonen, P., Trestian, R., & Ghinea, G. (2019). A comparison of reinforcement learning algorithms in fairness-oriented OFDMA schedulers. Information, 10(10), 315. https://doi.org/10.3390/info10100315

Due to large-scale control problems in 5G access networks, the complexity of radio resource management is expected to increase significantly. Reinforcement learning is seen as a promising solution that can enable intelligent decision-making and reduc... Read More about A comparison of reinforcement learning algorithms in fairness-oriented OFDMA schedulers.

Monitoring the performance of petrochemical organizations in Saudi Arabia using data envelopment analysis (2019)
Journal Article
Alidrisi, H., Aydin, M. E., Bafail, A. O., Abdulal, R., & Karuvatt, S. A. (2019). Monitoring the performance of petrochemical organizations in Saudi Arabia using data envelopment analysis. Mathematics, 7(6), 519. https://doi.org/10.3390/math7060519

The petrochemical industry plays a crucial role in the economy of the Kingdom of Saudi Arabia. Therefore, the effectiveness and efficiency of this industry is of high importance. Data envelopment analysis (DEA) is found to be more acceptable in measu... Read More about Monitoring the performance of petrochemical organizations in Saudi Arabia using data envelopment analysis.