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All Outputs (101)

Error-type -A novel set of software metrics for software fault prediction (2023)
Journal Article
Phung, K., Ogunshile, E., & Aydin, M. (2023). Error-type -A novel set of software metrics for software fault prediction. IEEE Access, 11, 30562-30574. https://doi.org/10.1109/ACCESS.2023.3262411

In software development, identifying software faults is an important task. The presence of faults not only reduces the quality of the software, but also increases the cost of development life cycle. Fault identification can be performed by analysing... Read More about Error-type -A novel set of software metrics for software fault prediction.

Modelling interrelationship between diseases with communicating stream x-machines (2022)
Journal Article
Jayatilake, D., Phung, K., Ogunshile, E., & Aydin, M. (2022). Modelling interrelationship between diseases with communicating stream x-machines. Proceedings of the Institute for System Programming of the RAS, 34(6), 147-164. https://doi.org/10.15514/ispras-2022-34%286%29-11

The world is moving towards alternative medicine and behavioural alteration for treating, managing, and preventing chronical diseases. In the last few decades, diagrammatical models have been extensively used to describe and understand the behaviou... Read More about Modelling interrelationship between diseases with communicating stream x-machines.

Problem classification for tailored help desk auto replies (2022)
Conference Proceeding
Nicholls, R., Fellows, R., Battle, S., & Ihshaish, H. (2022). Problem classification for tailored help desk auto replies. In E. Pimenidis, P. Angelov, C. Jayne, A. Papaleonidas, & M. Aydin (Eds.), Artificial Neural Networks and Machine Learning – ICANN 2022 (445-454). https://doi.org/10.1007/978-3-031-15937-4_37

IT helpdesks are charged with the task of responding quickly to user queries. To give the user confidence that their query matters, the helpdesk will auto-reply to the user with confirmation that their query has been received and logged. This auto-re... Read More about Problem classification for tailored help desk auto replies.

Analysing the predictivity of features to characterise the search space (2022)
Conference Proceeding
Durgut, R., Aydin, M. E., Ihshaish, H., & Rakib, A. (2022). Analysing the predictivity of features to characterise the search space. In E. Pimenidis, P. Angelov, C. Jayne, A. Papaleonidas, & M. Aydin (Eds.), Artificial Neural Networks and Machine Learning – ICANN 2022 31st International Conference on Artificial Neural Networks, Bristol, UK, September 6–9, 2022, Proceedings; Part IV (1-13). https://doi.org/10.1007/978-3-031-15937-4_1

Exploring search spaces is one of the most unpredictable challenges that has attracted the interest of researchers for decades. One way to handle unpredictability is to characterise the search spaces and take actions accordingly. A well-characterised... Read More about Analysing the predictivity of features to characterise the search space.

Development of communicating stream x-machine tool for modeling and generating test cases for automated teller machine (2022)
Presentation / Conference
Adewale Sanusi, B., Ogunshile, E., Aydin, M., Olatunde Olabiyisi, S., & Oyedepo Oyediran, M. (2022, August). Development of communicating stream x-machine tool for modeling and generating test cases for automated teller machine. Paper presented at 9th International Conference on Computer Science and Information Technology (CSIT 2022), Chennai, India

The improvement of this paper takes advantage of the existing formal method called Stream X-Machine by optimizing the theory and applying it to practice in a large-scale system. This optimized formal approach called Communicating Stream X-Machine (CS... Read More about Development of communicating stream x-machine tool for modeling and generating test cases for automated teller machine.

A strategy-based algorithm for moving targets in an environment with multiple agents (2022)
Journal Article
Afzalov, A., Lotfi, A., Inden, B., & Aydin, M. E. (2022). A strategy-based algorithm for moving targets in an environment with multiple agents. SN Computer Science, 3(6), 435. https://doi.org/10.1007/s42979-022-01302-x

Most studies in the field of search algorithms have only focused on pursuing agents, while comparatively less attention has been paid to target algorithms that employ strategies to evade multiple pursuing agents. In this study, a state-of-the-art tar... Read More about A strategy-based algorithm for moving targets in an environment with multiple agents.

Multi strategy search with crow search algorithm (2022)
Book Chapter
Durgut, R., & Aydin, M. E. (in press). Multi strategy search with crow search algorithm. In N. Vakhania (Ed.), Optimization Algorithms. IntechOpen. https://doi.org/10.5772/intechopen.102862

Crow Search Algorithm (CSA) is one of the recently proposed swarm intelligence algorithms developed inspiring of the social behaviour of crow flocks. One of the drawbacks of the original CSA is that it tends to randomly select a neighbour on search s... Read More about Multi strategy search with crow search algorithm.

Transfer learning for operator selection: A reinforcement learning approach (2022)
Journal Article
Durgut, R., Aydin, M. E., & Rakib, A. (2022). Transfer learning for operator selection: A reinforcement learning approach. Algorithms, 15(1), Article 24. https://doi.org/10.3390/a15010024

In the past two decades, metaheuristic optimisation algorithms (MOAs) have been increasingly popular, particularly in logistic, science, and engineering problems. The fundamental characteristics of such algorithms are that they are dependent on a par... Read More about Transfer learning for operator selection: A reinforcement learning approach.

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.

A Stream X-Machine tool for modelling and generating test cases for chronic diseases based on state-counting approach (2021)
Journal Article
Phung, K., Jayatilake, D., Ogunshile, E., & Aydin, M. (2021). A Stream X-Machine tool for modelling and generating test cases for chronic diseases based on state-counting approach. Programming and Computer Software, 47(8), 765-777. https://doi.org/10.1134/S0361768821080211

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 novel software fault prediction approach to predict error-type proneness in the Java programs using Stream X-Machine and machine learning (2021)
Conference Proceeding
Phung, K., Ogunshile, E., & Aydin, M. (2021). A novel software fault prediction approach to predict error-type proneness in the Java programs using Stream X-Machine and machine learning. In 2021 9th International Conference in Software Engineering Research and Innovation (CONISOFT) (168-179). https://doi.org/10.1109/CONISOFT52520.2021.00032

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
Jayatilake, S., Ogunshile, E., Aydin, M., & Phung, K. (2021). Modeling diseases with Stream X Machine. In 2021 9th International Conference in Software Engineering Research and Innovation (CONISOFT) (61-68). https://doi.org/10.1109/CONISOFT52520.2021.00020

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 accurac... Read More about Modeling diseases with Stream X Machine.

Adaptive operator selection with reinforcement learning (2021)
Journal Article
Durgut, R., Aydin, M. E., & Atli, I. (2021). Adaptive operator selection with reinforcement learning. Information Sciences, 581, 773-790. https://doi.org/10.1016/j.ins.2021.10.025

Operator selection plays a crucial role in the efficiency of heuristic-based problem solving algorithms, especially, when a pool of operators is used to let algorithms dynamically select operators to produce new candidate solutions. A sequence of sel... Read More about Adaptive operator selection with reinforcement learning.

Adaptive binary artificial bee colony for multi-dimensional knapsack problem (2021)
Journal Article
Durgut, R., & Aydın, M. E. (2021). Adaptive binary artificial bee colony for multi-dimensional knapsack problem. Journal of Gazi University Faculty of Engineering and Architecture, 36(4), 2333-2348. https://doi.org/10.17341/gazimmfd.804858

Purpose: The purpose of the study is to investigate how to solve for multi-dimensional knapsack problems better with higher robustness using binary artificial bee colony algorithms. Theory and Methods: The efficiency and effectiveness of metaheuristi... Read More about Adaptive binary artificial bee colony for multi-dimensional knapsack problem.

Reinforcement learning-based adaptive operator selection (2021)
Conference Proceeding
Durgut, R., & Aydin, M. E. (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 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 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.