Mr Habeeb Balogun


2024

Exploratory Analysis of Machine Learning Methods for Total Organic Carbon Prediction Using Well-Log Data of Kolmani Field
Longman, Fodio S., Balogun, Habeeb, Ojulari, Rasheed O., Olatomiwa, Olaniyi J., Balarabe, Husaini J., Edeh, Ifeanyichukwu S. and Joshua, Olabisi O. 2024. Exploratory Analysis of Machine Learning Methods for Total Organic Carbon Prediction Using Well-Log Data of Kolmani Field. IEEE 14th International Conference on Pattern Recognition Systems (ICPRS). London, United Kingdom 15 - 18 Jul 2024 IEEE . https://doi.org/10.1109/icprs62101.2024.10677822

2024

Artificial intelligence for deconstruction: Current state, challenges, and opportunities
Balogun, H., Alaka, H., Demir, E., Egwim, C.N, Olu-Ajayi, R., Sulaimon, I. and Oseghale, R. 2024. Artificial intelligence for deconstruction: Current state, challenges, and opportunities. Automation in Construction. 166 105641. https://doi.org/10.1016/j.autcon.2024.105641

2024

Critical factors for assessing building deconstructability: Exploratory and confirmatory factor analysis
Habeeb Balogun, Hafiz Alaka, Saheed Ajayi and Christian Nnaemeka Egwim 2024. Critical factors for assessing building deconstructability: Exploratory and confirmatory factor analysis. Cleaner Engineering and Technology. 21 100790. https://doi.org/10.1016/j.clet.2024.100790

2024

Artificial Intelligence in the Construction Industry: A Systematic Review of the Entire Construction Value Chain Lifecycle
Christian Nnaemeka Egwim,, Hafiz Alaka,, Eren Demir, Habbeb Balogun, Razak Olu-Ajayi, Ismail Sulaimon, Godoyon Wusu, Wasiu Yusuf and Adegoke A. Muideen 2024. Artificial Intelligence in the Construction Industry: A Systematic Review of the Entire Construction Value Chain Lifecycle. Energies. 17 (1) 182. https://doi.org/10.3390/en17010182

2023

Building energy performance prediction: A reliability analysis and evaluation of feature selection methods
Olu-Ajayi, R., Alaka, H., Sulaimon, I., Balogun, H., Wusu, G., Yusuf, W. and Adegoke, M. 2023. Building energy performance prediction: A reliability analysis and evaluation of feature selection methods. Expert Systems with Applications. 225 120109. https://doi.org/10.1016/j.eswa.2023.120109

2023

Ensemble of ensembles for fine particulate matter pollution prediction using big data analytics and IoT emission sensors
Christian Nnaemeka Egwim, Hafiz Alaka, Youlu Pan, Balogun, H., Saheed Ajayi, Abdul Hye and Oluwapelumi Oluwaseun Egunjobi 2023. Ensemble of ensembles for fine particulate matter pollution prediction using big data analytics and IoT emission sensors. Journal of Engineering, Design and Technology. Advanced online publication. https://doi.org/10.1108/JEDT-07-2022-0379

2023

Extraction of underlying factors causing construction projects delay in Nigeria
Egwim, C.N., Alaka, H., Toriola-Coker, L.O., Balogun, H., Ajayi, S. and Oseghale, R. 2023. Extraction of underlying factors causing construction projects delay in Nigeria. Journal of Engineering, Design and Technology. 21 (5), pp. 1323-1342. https://doi.org/10.1108/jedt-04-2021-0211

2023

Systematic review of drivers influencing building deconstructability: Towards a construct-based conceptual framework
Balogun, H., Alaka, H., Egwim, C.N. and Ajayi, S. 2023. Systematic review of drivers influencing building deconstructability: Towards a construct-based conceptual framework. Waste Management and Research. 41 (3), pp. 512-530. https://doi.org/10.1177/0734242x221124078

2021

Applied artificial intelligence for predicting construction projects delay
Christian Nnaemeka Egwim, Hafiz Alaka, Luqman Olalekan Toriola-Coker, Habeeb Balogun and Funlade Sunmola 2021. Applied artificial intelligence for predicting construction projects delay. Machine Learning with Applications. 6 100166. https://doi.org/10.1016/j.mlwa.2021.100166

2021

Boruta-grid-search least square support vector machine for NO2 pollution prediction using big data analytics and IoT emission sensors
Balogun, H., Alaka, H. and Egwim, C.N. 2021. Boruta-grid-search least square support vector machine for NO2 pollution prediction using big data analytics and IoT emission sensors. Applied Computing and Informatics. Advanced online publication. https://doi.org/10.1108/aci-04-2021-0092


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