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Architecture and Planning (with Foundation Year) - BA(Hons)
Our BA(Hons) Architecture and Planning (with Foundation Year) is accredited by RIBA. We're currently seeking re-accreditation from the RTPI.
Architecture - MArch
Study our Master of Architecture course to gain experience to apply to your architectural practice. Specialise and conduct research in an area of your choice.
Apply for an international study exchange - International study exchange
Find out how to apply for a study abroad exchange at UWE Bristol for an academic year or a semester.
Environmental Science (with Foundation Year) - BSc(Hons)
BSc(Hons) Environmental Science (with Foundation Year) is accredited by the Institution of Environmental Sciences and teaches you to tackle environmental issues
International Law and Security - LLM
Study our LLM International Law and Security to develop your legal career as a specialist in the global legal system, national security and conflict resolution.
Clinical Biochemistry - Professional/Short course
Learn to interpret biomedical data in the investigation and diagnosis of disease in this Clinical Biochemistry course.
Air Quality Modelling - Professional course
Learn about dispersion models theory and practice to replicate the behaviour of atmospheric pollution in the Air Quality Modelling course.
An explanation-based approach for experiment reproducibility in recommender systems (2019)
Journal Article
Polatidis, N., Papaleonidas, A., Pimenidis, E., & Iliadis, L. (in press). An explanation-based approach for experiment reproducibility in recommender systems. Neural Computing and Applications, https://doi.org/10.1007/s00521-019-04274-x
© 2019, Springer-Verlag London Ltd., part of Springer Nature. The offline evaluation of recommender systems is typically based on accuracy metrics such as the Mean Absolute Error and the Root Mean Squared Error for error rating prediction and Precisi...
about An explanation-based approach for experiment reproducibility in recommender systems.
Optimisation of resource management in construction projects: A big data approach (2019)
Journal Article
Kusimo, H., Oyedele, L., Akinade, O., Oyedele, A., Abioye, S., Agboola, A., & Mohammed-Yakub, N. (2019). Optimisation of resource management in construction projects: A big data approach. World Journal of Science, Technology and Sustainable Development, 16(2), 82-93. https://doi.org/10.1108/WJSTSD-05-2018-0044
Resource management is one of the key factors for achieving project success, which includes the management of project teams, labour and plant and equipment needed to deliver the project. This study aims to identify challenges facing resource manageme...
about Optimisation of resource management in construction projects: A big data approach.