Enhanced façade design: A data-driven approach for decision analysis based on past experiences. (March 2021)

• Record Type: Journal Article
• Authors: Moghtadernejad, Saviz; Chouinard, Luc E.; Mirza, M. Saeed
• Is Part Of: Developments in the built environment. Volume 5(2021)
• Publication Date: 2021-03
• Subjects: Sustainable façade design -- Multi-criteria decision-making methods -- Neural networks -- Principal component analysis -- High-performance buildings; Civil engineering -- Periodicals; Sustainable construction -- Periodicals; 624.05
• DOI: 10.1016/j.dibe.2020.100038
• Languages: English
• ISSNs: 2666-1659

Abstract

Abstract: The selection of an optimal building façade system is a challenging process that can be facilitated by using decision-analysis methods. However, current commonly-used decision-analysis tools in civil engineering cannot deal with the interactions among multiple design criteria. The Choquet integral is the only well-known method capable of accounting for such interactions. However, the process of assigning the fuzzy measures (importance weights) for this method is complex, particularly when there is a large number of criteria be considered. This paper proposes two supervised methods to estimate these fuzzy measures. The first method estimates the relative importance weights by using a statistical approach based on Principal Component Analysis, while the second method is elicited from a machine learning algorithm using Neural Networks. These two methods are used in an illustrative example to find the fuzzy measures related to façade design with respect to four criteria; and their merits and limitations are discussed. Highlights: Improving the facade design procedure by quantifying the intuitions of the designer. Consideration of the interactions among design criteria in decision-making. Supervised approaches to estimate the fuzzy measures related to Choquet integral. Estimation of importance weights of the design criteria and the related interactions.