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| − | #REDIRECT [[]] | + | #REDIRECT [[An Introspective Approach to Apartment Design]] |
| − | [[Category:DCIO]]
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| − | [[Category:DCIO2020]]
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| − | [[Category:DCIO Proceedings]]
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| − | [[Category:Conferences]]
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| − | =An Introspective Approach to Apartment Design=
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| − | by [[OLIVER GREEN]]
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| − | This paper outlines the development of a residential layout recommendation tool at Allford Hall Monaghan Morris, a large architecture firm based in London. Using software development and machine learning techniques, the firm developed a plugin for Autodesk Revit to assist architects by allowing them to cross-reference any empty space against the firm’s library of completed apartment designs. Nicknamed ‘Homegrown’, this tool recommends apartment layouts used in similar spaces. Any apartment chosen by the user is then automatically reconstructed, adapted and post-rationalised to fit the target space.
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| − | To further enhance the efficacy of this tool, feedback was collected from the firm’s architects which was then used to refine the recommendation algorithm’s feature weightings using various regression techniques.
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| − | This paper gives an overview of the tool’s development process and focuses particularly on its spatial analysis algorithm, which was developed alongside AHMM’s architectural design teams. It attempts to answer the question: can architecture firms use heuristic techniques to develop new residential layouts based on existing designs, rather than generating them from first principles?
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| − | =Keywords=
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| − | [[Design Automation]], [[Recommendation]], [[Space Planning]], [[Architecture]], [[Residential Design]], [[Machine Learning]], [[Feature Importance]], [[Regression]].
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| − | =Reference=
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