Learning the Link between Architectural Form and Structural Efficiency: A Supervised Machine Learning Approach †
Abstract
:1. Introduction
2. Proposed Methodology
2.1. Architectural Form Generation
2.2. Structural Results
2.3. Supervised Machine Learning—A Classification Approach
2.4. Classification Algorithms and Hyperparameter Optimization
3. Results of the ML Classification
3.1. k-Nearest Neighbors
3.2. Support Vector Machine
3.3. Decision Tree
3.4. Ensemble Classifier
3.5. Naïve Bayes
3.6. Discriminant Analysis
4. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Conflicts of Interest
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Kazemi, P.; Ghisi, A.; Mariani, S. Learning the Link between Architectural Form and Structural Efficiency: A Supervised Machine Learning Approach. Comput. Sci. Math. Forum 2022, 2, 18. https://doi.org/10.3390/IOCA2021-10891
Kazemi P, Ghisi A, Mariani S. Learning the Link between Architectural Form and Structural Efficiency: A Supervised Machine Learning Approach. Computer Sciences & Mathematics Forum. 2022; 2(1):18. https://doi.org/10.3390/IOCA2021-10891
Chicago/Turabian StyleKazemi, Pooyan, Aldo Ghisi, and Stefano Mariani. 2022. "Learning the Link between Architectural Form and Structural Efficiency: A Supervised Machine Learning Approach" Computer Sciences & Mathematics Forum 2, no. 1: 18. https://doi.org/10.3390/IOCA2021-10891
APA StyleKazemi, P., Ghisi, A., & Mariani, S. (2022). Learning the Link between Architectural Form and Structural Efficiency: A Supervised Machine Learning Approach. Computer Sciences & Mathematics Forum, 2(1), 18. https://doi.org/10.3390/IOCA2021-10891