All Outputs (8)

Adaptive swarm optimisation assisted surrogate model for pipeline leak detection and characterisation. (2023)
Thesis
ADEGBOYE, M.A. 2023. Adaptive swarm optimisation assisted surrogate model for pipeline leak detection and characterisation. Robert Gordon University, PhD thesis. Hosted on OpenAIR [online]. Available from: https://doi.org/10.48526/rgu-wt-2071535

Pipelines are often subject to leakage due to ageing, corrosion and weld defects. It is difficult to avoid pipeline leakage as the sources of leaks are diverse. Various pipeline leakage detection methods, including fibre optic, pressure point analysi... Read More about Adaptive swarm optimisation assisted surrogate model for pipeline leak detection and characterisation..

Simple deterministic selection-based genetic algorithm for hyperparameter tuning of machine learning models. (2022)
Journal Article
RAJI, I.D., BELLO-SALAU, H., UMOH, I.J., ONUMANYI, A.J., ADEGBOYE, M.A. and SALAWUDEEN, A.T. 2022. Simple deterministic selection-based genetic algorithm for hyperparameter tuning of machine learning models. Applied sciences [online], 12(3), article 1186. Available from: https://doi.org/10.3390/app12031186

Hyperparameter tuning is a critical function necessary for the effective deployment of most machine learning (ML) algorithms. It is used to find the optimal hyperparameter settings of an ML algorithm in order to improve its overall output performance... Read More about Simple deterministic selection-based genetic algorithm for hyperparameter tuning of machine learning models..

Machine learning methods for sign language recognition: a critical review and analysis. (2021)
Journal Article
ADEYANJU, I.A., BELLO, O.O. and ADEGBOYE, M.A. 2021. Machine learning methods for sign language recognition: a critical review and analysis. Intelligent systems with applications [online], 12, article 200056. Available from: https://doi.org/10.1016/j.iswa.2021.200056

Sign language is an essential tool to bridge the communication gap between normal and hearing-impaired people. However, the diversity of over 7000 present-day sign languages with variability in motion position, hand shape, and position of body parts... Read More about Machine learning methods for sign language recognition: a critical review and analysis..

Numerical study of pipeline leak detection for gas-liquid stratified flow. (2021)
Journal Article
ADEGBOYE, M.A., KARNIK, A. and FUNG, W.-K. 2021. Numerical study of pipeline leak detection for gas-liquid stratified flow. Journal of natural gas science and engineering [online], 94, article 104054. Available from: https://doi.org/10.1016/j.jngse.2021.104054

Multiphase flows are of paramount importance in the oil and gas industry, considering that most petroleum industries produce and transport oil and gas simultaneously. However, systematic research on pipeline leakage conveying more than one phase at a... Read More about Numerical study of pipeline leak detection for gas-liquid stratified flow..

Incorporating Intelligence in Fish Feeding System for Dispensing Feed Based on Fish Feeding Intensity (2020)
Journal Article
ADEGBOYE, M.A., AIBINU, A.M., KOLO, J.G., ALIYU, I., FOLORUNSO, T.A. and LEE, S.-H. 2020. Incorporating intelligence in fish feeding system for dispensing feed based on fish feeding intensity. IEEE access [online], 8, pages 91948-91960. Available from: https://doi.org/10.1109/ACCESS.2020.2994442

The amount of feed dispense to match fish appetite plays a significant role in increasing fish cultivation. However, measuring the quantity of fish feed intake remains a critical challenge. To addressed this problem, this paper proposed an intelligen... Read More about Incorporating Intelligence in Fish Feeding System for Dispensing Feed Based on Fish Feeding Intensity.

Recent advances in pipeline monitoring and oil leakage detection technologies: principles and approaches. (2019)
Journal Article
ADEGBOYE, M.A., FUNG, W.-K. and KARNIK, A. 2019. Recent advances in pipeline monitoring and oil leakage detection technologies: principles and approaches. Sensors [online], 19(11), article ID 2548. Available from: https://doi.org/10.3390/s19112548

Pipelines are widely used for the transportation of hydrocarbon fluids over millions of miles all over the world. The structures of the pipelines are designed to withstand several environmental loading conditions to ensure safe and reliable distribut... Read More about Recent advances in pipeline monitoring and oil leakage detection technologies: principles and approaches..

Modeling and implementation of smart home and self-control window using FPGA and Petri Net.
Presentation / Conference Contribution
AJAO, L.A., AGAJO, J., UMAR, B.U., AGBOADE, T.T. and ADEGBOYE, M.A. 2020. Modeling and implementation of smart home and self-control window using FPGA and Petri Net. In Proceedings of 7th IEEE (Institute of Electrical and Electronics Engineers) PES/IAS (Power and Energy Society/Industrial Applications Society) PowerAfrica 2020 (IEEE PES/IAS PowerAfrical 2020): sustainable and smart energy revolutions for powering Africa, 25-28 August 2020, [virtual conference]. Piscataway: IEEE [online], article 9219925. Available from: https://doi.org/10.1109/PowerAfrica49420.2020.9219925

The function of the window is to provide comfort for the householders by regulating the indoor environment. However, most of the residence windows are still controlled manually. Although, a quite number of automated windows based on the Internet of T... Read More about Modeling and implementation of smart home and self-control window using FPGA and Petri Net..

Pipeline leakage detection and characterisation with adaptive surrogate modelling using particle swarm optimisation.
Presentation / Conference Contribution
ADEGBOYE, M.A., KARNIK, A., FUNG, W.-K. and PRABHU, R. 2022. Pipeline leakage detection and characterisation with adaptive surrogate modelling using particle swarm optimisation. In Proceedings of the 9th International conference on soft computing and machine intelligence 2022 (ISCMI 2022), 26-27 November 2022, Toronto, Candada. Piscataway: IEEE [online], pages 129-134. Available from: https://doi.org/10.1109/iscmi56532.2022.10068436

Pipelines are often subject to leakage due to ageing, corrosion, and weld defects, and it is difficult to avoid as the sources of leakages are diverse. Several studies have demonstrated the applicability of the machine learning model for the timely p... Read More about Pipeline leakage detection and characterisation with adaptive surrogate modelling using particle swarm optimisation..