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A holistic sustainability framework for oil terminals: The case of China (2020)
Journal Article
Wang, X., Liu, S., Xu, J., & Roe, M. (2020). A holistic sustainability framework for oil terminals: The case of China. International Journal of Shipping and Transport Logistics, 12(6), 521-542. https://doi.org/10.1504/IJSTL.2020.10019947

This research provides a sustainability framework for the Chinese oil terminal sustainability performance evaluation. Due to the lack of existing holistic oil terminal sustainability research and the increasing demand for sustainability pursuits, the... Read More about A holistic sustainability framework for oil terminals: The case of China.

Deep learning model for demolition waste prediction in a circular economy (2020)
Journal Article
Akanbi, L. A., Oyedele, A. O., Oyedele, L. O., & Salami, R. O. (2020). Deep learning model for demolition waste prediction in a circular economy. Journal of Cleaner Production, 274, https://doi.org/10.1016/j.jclepro.2020.122843

An essential requirement for a successful circular economy is the continuous use of materials. Planning for building materials reuse at the end-of-life of buildings is usually a difficult task because limited time are usually made available for build... Read More about Deep learning model for demolition waste prediction in a circular economy.

Genetic algorithm-determined deep feedforward neural network architecture for predicting electricity consumption in real buildings (2020)
Journal Article
Luo, X. J., Oyedele, L. O., Ajayi, A. O., Akinade, O. O., Delgado, J. M. D., Owolabi, H. A., & Ahmed, A. (2020). Genetic algorithm-determined deep feedforward neural network architecture for predicting electricity consumption in real buildings. Energy and AI, 2, https://doi.org/10.1016/j.egyai.2020.100015

A genetic algorithm-determined deep feedforward neural network architecture (GA-DFNN) is proposed for both day-ahead hourly and week-ahead daily electricity consumption of a real-world campus building in the United Kingdom. Due to the comprehensive r... Read More about Genetic algorithm-determined deep feedforward neural network architecture for predicting electricity consumption in real buildings.

Feature extraction and genetic algorithm enhanced adaptive deep neural network for energy consumption prediction in buildings (2020)
Journal Article
Luo, X. J., Oyedele, L. O., Ajayi, A. O., Akinade, O. O., Owolabi, H. A., & Ahmed, A. (2020). Feature extraction and genetic algorithm enhanced adaptive deep neural network for energy consumption prediction in buildings. Renewable and Sustainable Energy Reviews, 131, https://doi.org/10.1016/j.rser.2020.109980

Accurate forecast of energy consumption is essential in building energy management. Owing to the variation of outdoor weather condition among different seasons, year-round historical weather profile is needed to investigate its feature thoroughly. Da... Read More about Feature extraction and genetic algorithm enhanced adaptive deep neural network for energy consumption prediction in buildings.

Big data innovation and diffusion in projects teams: Towards a conflict prevention culture (2020)
Journal Article
Oyedele, A., Owolabi, H. A., Oyedele, L. O., & Olawale, O. A. (2020). Big data innovation and diffusion in projects teams: Towards a conflict prevention culture. Developments in the Built Environment, 3, https://doi.org/10.1016/j.dibe.2020.100016

Despite the enormous literature on how team conflicts can be managed and resolved, this study diverges, by examining factors that facilitate conflict prevention culture in project teams, especially when introducing Big Data Technology. Relying on fin... Read More about Big data innovation and diffusion in projects teams: Towards a conflict prevention culture.

Project reputation in construction: A process-based perspective of construction practitioners in the UK (2020)
Journal Article
Olawale, O., Oyedele, L., Owolabi, H., Gbadamosi, A., & Kusimo, H. (in press). Project reputation in construction: A process-based perspective of construction practitioners in the UK. International Journal of Construction Management, https://doi.org/10.1080/15623599.2020.1783598

The overall aim of this study is to elicit the perspective of practitioners (e.g., architects, civil engineers, building engineers, structural engineers and quantity surveyors) on the process-related factors influencing the project reputation of cons... Read More about Project reputation in construction: A process-based perspective of construction practitioners in the UK.

Human error in autonomous underwater vehicle deployment: A system dynamics approach (2020)
Journal Article
Loh, T. Y., Brito, M. P., Bose, N., Xu, J., & Tenekedjiev, K. (2020). Human error in autonomous underwater vehicle deployment: A system dynamics approach. Risk Analysis, 40(6), 1258-1278. https://doi.org/10.1111/risa.13467

The use of autonomous underwater vehicles (AUVs) for various applications have grown with maturing technology and improved accessibility. The deployment of AUVs for under-ice marine science research in the Antarctic is one such example. However, a hi... Read More about Human error in autonomous underwater vehicle deployment: A system dynamics approach.

The international legal regime governing shipboard LNG (2020)
Book Chapter
Xu, J., & Mukerhjee, P. K. (2020). The international legal regime governing shipboard LNG. In P. K. Mukherjee, M. Q. Mejia, & J. Xu (Eds.), Maritime Law in Motion. , (691-702). Springer. https://doi.org/10.1007/978-3-030-31749-2_33

The Chapter addresses the international legal regime governing shipboard LNG which could be carried on board as cargo or fuel. The discussion touches upon both the regulatory law element as well as the private law dimension of the regime. On the regu... Read More about The international legal regime governing shipboard LNG.

A hybrid fuzzy system dynamics approach for risk analysis of AUV operations (2020)
Journal Article
Loh, T. Y., Brito, M. P., Bose, N., Xu, J., Nikolova, N., & Tenekedjiev, K. (2020). A hybrid fuzzy system dynamics approach for risk analysis of AUV operations. Journal of Advanced Computational Intelligence and Intelligent Informatics, 24(1), 26-39. https://doi.org/10.20965/jaciii.2020.p0026

© 2020 Fuji Technology Press. All rights reserved. The maturing of autonomous technology has fostered a rapid expansion in the use of Autonomous Underwater Vehicles (AUVs). To prevent the loss of AUVs during deployments, existing risk analysis approa... Read More about A hybrid fuzzy system dynamics approach for risk analysis of AUV operations.