Investigating the use of Machine Learning for Resource Intensive Agent-Based Simulation and Optimisation of Domestic Energy Retrofit Adoption

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Investigating the use of Machine Learning for Resource Intensive Agent-Based Simulation and Optimisation of Domestic Energy Retrofit Adoption

The existing domestic urban built environment contributes significantly to the environ- mental issues facing the international community. Whole house energy retrofits per- formed on this stock are a key tool for the mitigation of greenhouse gas emissions. As such, researchers have built a set of bot...

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Bibliographic Details
Main Author:	Hey, James
Format:	Thesis (University of Nottingham only)
Language:	English
Published:	2022
Subjects:	energy use energy use modelling machine learning neural networks
Online Access:	https://eprints.nottingham.ac.uk/69527/

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