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Pandemic management with social media analytics (2021)
Book Chapter
Sabuncu, I., & Aydin, M. E. (2021). Pandemic management with social media analytics. In Data Science Advancements in Pandemic and Outbreak Management (78-107). IGI Global. https://doi.org/10.4018/978-1-7998-6736-4.ch005

Social media analytics appears as one of recently developing disciplines that helps understand public perception, reaction, and emerging developments. Particularly, pandemics are one of overwhelming phenomena that push public concerns and necessitate... Read More about Pandemic management with social media analytics.

Reinforcement learning-based adaptive operator selection (2021)
Conference Proceeding
Durgut, R., & Aydin, M. (2021). Reinforcement learning-based adaptive operator selection. In B. Dorronsoro, L. Amodeo, M. Pavone, & P. Ruiz (Eds.), https://doi.org/10.1007/978-3-030-85672-4_3

Metaheuristic and swarm intelligence approaches require devising optimisation algorithms with operators to let produce neighbouring solutions to conduct a move. The efficiency of algorithms using single operator remains recessive in comparison with t... Read More about Reinforcement learning-based adaptive operator selection.

A Stream X-Machine tool for modelling and generating test cases for chronic diseases based on state-counting approach (2021)
Journal Article
Ogunshile, E., Phung, K., Jayatilake, D., & Aydin, M. (in press). A Stream X-Machine tool for modelling and generating test cases for chronic diseases based on state-counting approach. Programming and Computer Software,

In the biomedical domain, diagrammatical models have been extensively used to describe and understand the behaviour of biological organisms (biological agents) for decades. Although these models are simple and comprehensive, they can only offer a sta... Read More about A Stream X-Machine tool for modelling and generating test cases for chronic diseases based on state-counting approach.

A strategic search algorithm in multi-agent and multiple target environment (2021)
Conference Proceeding
Afzalov, A., Lotfi, A., & Aydin, M. E. (2021). A strategic search algorithm in multi-agent and multiple target environment. In E. Chew, A. P. Abdul Majeed, P. Liu, J. Platts, H. Myung, J. Kim, & J. Kim (Eds.), RiTA 2020 (195-204). https://doi.org/10.1007/978-981-16-4803-8_21

The aim of this study is to investigate how to solve the path-planning problem of multiple competing players towards moving targets within a dynamically changing environment. A novel approach is needed to exceed the classical solutions for single or... Read More about A strategic search algorithm in multi-agent and multiple target environment.

A novel software fault prediction approach to predict error-type proneness in the Java programs using Stream X-Machine and machine learning (2021)
Conference Proceeding
Ogunshile, E., Phung, K., & Aydin, M. (in press). A novel software fault prediction approach to predict error-type proneness in the Java programs using Stream X-Machine and machine learning

Software fault prediction makes software quality assurance process more efficient and economic. Most of the works related to software fault prediction have mainly focused on classifying software modules as faulty or not, which does not produce suffic... Read More about A novel software fault prediction approach to predict error-type proneness in the Java programs using Stream X-Machine and machine learning.

Modeling diseases with Stream X Machine (2021)
Conference Proceeding
Ogunshile, E., Jayatilake, S., Aydin, M., & Phung, K. (in press). Modeling diseases with Stream X Machine

At present the world is moving towards alternative medicine and behavioural alteration for treating, managing and preventing chronical diseases. With the individuality of the human beings has added more complexity in a domain where very high accuracy... Read More about Modeling diseases with Stream X Machine.

A comparative analysis for binary search operators used in artificial bee colony (2021)
Conference Proceeding
Atli, I., Durgut, R., & Aydin, M. E. (2021). A comparative analysis for binary search operators used in artificial bee colony. In 2021 29th Signal Processing and Communications Applications Conference (SIU)https://doi.org/10.1109/SIU53274.2021.9477907

Metaheuristic optimization algorithms are developed to find the best or near-best solutions within a reasonable time frame utilizing various neighbourhood functions (i.e., operators). Variety of studies have been proposed for structural modifications... Read More about A comparative analysis for binary search operators used in artificial bee colony.

Multi-agent path planning approach using assignment strategy variations in pursuit of moving targets (2021)
Conference Proceeding
Afzalov, A., He, J., Lotfi, A., & Aydin, M. E. (2021). Multi-agent path planning approach using assignment strategy variations in pursuit of moving targets. In G. Jezic, J. Chen-Burger, M. Kusek, R. Sperka, R. Howlett, & L. Jain (Eds.), Agents and Multi-Agent Systems: Technologies and Applications 2021 (451-463). https://doi.org/10.1007/978-981-16-2994-5_38

This study aims to investigate the problem of assignment strategies for multiple agents. In multi-agent scenarios, agents compute a path towards the goal, while these goal destinations in some cases are predefined in advance. The topic of assignment... Read More about Multi-agent path planning approach using assignment strategy variations in pursuit of moving targets.

Solving set union knapsack problems with adaptive binary artificial bee colony (2021)
Journal Article
Durgut, R., Yavuz, İ., & Aydin, M. (2021). Solving set union knapsack problems with adaptive binary artificial bee colony. Journal of Intelligent Systems: Theory and Applications, 4(1), 43-54. https://doi.org/10.38016/jista.854584

Meta-heuristic and swarm intelligence algorithms have long been used to provide approximate solutions to NP-Hard optimization problems. Especially when it comes to combinatorial and binary problems, operator functions used to generate neighbor soluti... Read More about Solving set union knapsack problems with adaptive binary artificial bee colony.

Multiple pursuers TrailMax algorithm for dynamic environments (2021)
Conference Proceeding
Afzalov, A., Lotfi, A., Inden, B., & Aydin, M. (2021). Multiple pursuers TrailMax algorithm for dynamic environments. In Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART. , (437-443). https://doi.org/10.5220/0010392404370443

Multi-agent multi-target search problems, where the targets are capable of movement, require sophisticated algorithms for near-optimal performance. While there are several algorithms for agent control, comparatively less attention has been paid to ne... Read More about Multiple pursuers TrailMax algorithm for dynamic environments.

Elicitation of the factors affecting electricity distribution efficiency using the fuzzy AHP method (2020)
Journal Article
Yiğit, V., Demir, N. N., Alidrisi, H., & Aydin, M. E. (2020). Elicitation of the factors affecting electricity distribution efficiency using the fuzzy AHP method. Mathematics, 9(1), 1-25. https://doi.org/10.3390/math9010082

Efficient and uninterrupted energy supply plays a crucial role in the quality of modern daily life, while it is obvious that the efficiency and performance of energy supply companies has a significant impact on energy supply itself and on determining... Read More about Elicitation of the factors affecting electricity distribution efficiency using the fuzzy AHP method.

Adaptive binary artificial bee colony algorithm (2020)
Journal Article
Durgut, R., & Aydin, M. E. (2021). Adaptive binary artificial bee colony algorithm. Applied Soft Computing, 101, https://doi.org/10.1016/j.asoc.2020.107054

Metaheuristics and swarm intelligence algorithms are bio-inspired algorithms, which have long standing track record of success in problem solving. Due to the nature and the complexity of the problems, problem solving approaches may not achieve the sa... Read More about Adaptive binary artificial bee colony algorithm.

Max-gain relay selection scheme for wireless networks (2020)
Journal Article
Ullah, S., Malik, M. H., Tuysuz, M. F., Hasnain, M., & Aydin, M. E. (2021). Max-gain relay selection scheme for wireless networks. International Journal of Engineering Science and Technology, 24(1), 183-191. https://doi.org/10.1016/j.jestch.2020.08.009

© 2020 Karabuk University Next generation wireless systems are supposed to handle high amount of data with broader coverage and high quality of service (QoS). When a signal travels from a source to destination, the signal quality may suffer from the... Read More about Max-gain relay selection scheme for wireless networks.

A multi agent-based approach for energy efficient water resource management (2020)
Journal Article
Aydin, M. E., & Keleş, R. (2021). A multi agent-based approach for energy efficient water resource management. Computers and Industrial Engineering, 151, https://doi.org/10.1016/j.cie.2020.106679

Water supply remains one of globally recognised challenging problems due to the scarcity in the water sources, the environmental concerns and hardness in access to clean and fresh water. Besides, energy consumption is also under focus as much as acce... Read More about A multi agent-based approach for energy efficient water resource management.

Feature selection with artificial bee colony algorithms for classifying Parkinson’s diseases (2020)
Conference Proceeding
Durgut, R., Baydilli, Y. Y., & Aydin, M. E. (2020). Feature selection with artificial bee colony algorithms for classifying Parkinson’s diseases. In Proceedings of the 21st EANN (Engineering Applications of Neural Networks) 2020 Conference. , (338-351). https://doi.org/10.1007/978-3-030-48791-1_26

Parkinson’s is a brain disease that affects the quality of human life significantly with very slow progresses. It is known that early diagnosis is of great importance to arrange relevant and efficient treatments. Data analytics and particularly predi... Read More about Feature selection with artificial bee colony algorithms for classifying Parkinson’s diseases.

QoE-based mobility-aware collaborative video streaming on the edge of 5G (2020)
Journal Article
Tuysuz, M. F., & Aydin, M. E. (2020). QoE-based mobility-aware collaborative video streaming on the edge of 5G. IEEE Transactions on Industrial Informatics, 16(11), 7115-7125. https://doi.org/10.1109/tii.2020.2972931

Today's Internet traffic is dominated by video streaming applications transmitted through wireless/cellular interfaces of mobile devices. Although ultrahigh-definition videos are now easily transmitted through mobile devices, video quality level that... Read More about QoE-based mobility-aware collaborative video streaming on the edge of 5G.

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.