CumInCAD is a Cumulative Index about publications in Computer Aided Architectural Design
supported by the sibling associations ACADIA, CAADRIA, eCAADe, SIGraDi, ASCAAD and CAAD futures

PDF papers
References
id ecaade2020_015
authors Yazici, Sevil
year 2020
title A machine-learning model driven by geometry, material and structural performance data in architectural design process
source Werner, L and Koering, D (eds.), Anthropologic: Architecture and Fabrication in the cognitive age - Proceedings of the 38th eCAADe Conference - Volume 1, TU Berlin, Berlin, Germany, 16-18 September 2020, pp. 411-418
summary Artificial Intelligence (AI), based on interpretation of data, influences various professions including architectural design today. Although research on integrating conceptual design with Machine Learning (ML) algorithms as a subset of the AI has been investigated previously, there is not a framework towards integration of architectural geometry with material properties and structural performance data towards decision making in the early-design phase. Undertaking performance simulations require significant amount of computation power and time. The aim of this research is to integrate ML algorithms into design process to achieve time efficiency and improve design results. The proposed workflow consists of three stages, including generation of the parametric model; running structural performance simulations to collect the data, and operating the ML algorithms, including Artificial Neural Network (ANN), Non-Linear Regression (NLR) and Gaussian Mixture (GM) for undertaking different tasks. The results underlined that the system generates relatively fast solutions with accuracy. Additionally, ML algorithms can assist generative design processes.
keywords Machine-learning; performance simulation; data-driven design; early-design phase
series eCAADe
email sevil.yazici@ozyegin.edu.tr
full text file.pdf (1,252,694 bytes)
references Content-type: text/plain
Details Citation Select
100%; open As, I., Pal, S. and Basu, P. (2018) Find in CUMINCAD Artificial intelligence in architecture: Generating conceptual design via deep learning , International Journal of Architectural Computing, 16(4), pp. 306-327

100%; open Brown, N.C and Mueller, C. T (2019) Find in CUMINCAD Design variable analysis and generation for performance-based parametric modeling in architectur , International Journal of Architectural Computing, 17(1), pp. 36-52

100%; open Chatzikonstantinou, I. and Sariyildiz, S. (2016) Find in CUMINCAD Approximation of simulation-derived visual comfort indicators in office spaces: a comparative study in machine learning , Architectural Science Review, vol. 59, No. 4, pp. 307-322

100%; open Derix, C. and Jagannath, P. (2014) Find in CUMINCAD Near Futures: Associative Archetypes , Architectural Design, 84(5), pp. 130-135

100%; open Karan, E. and Asadi, S. (2019) Find in CUMINCAD Intelligent designer: A computational approach to automating design of windows in buildings. , Automation in Construction, 102, pp. 160-169

100%; open Negroponte, N (1969) Find in CUMINCAD Toward a Theory of Architecture Machines , Journal of Architectural Education, 23, pp. 9-12

100%; open Shubert, B.O (1969) Find in CUMINCAD Bayesian Model of Decision-Making as a Result of Learning From Experience , Annals of Mathematical Statistics, 40, pp. 2127-2142

100%; open Storey, V. C. and Goldstein, R.C. (1993) Find in CUMINCAD Knowledge-Based Approaches to Database Design , MIS Quarterly, 17, pp. 25-46

100%; open Strobbe, T., Wyffels, F., Verstraeten, R., Meyer, R. D. and Campenhout, J. V. (2016) Find in CUMINCAD Automatic architectural style detection using one-class support vector machines and graph kernels , Automation in Construction, 69, pp. 1-10

100%; open Tamke, M. and Thomsen, M. R. (2018) Find in CUMINCAD Complex Modelling , International Journal of Architectural Computing, 16(2), pp. 87-90

100%; open Tamke, M., Nicholas, P., P. and Zwierzycki, M. (2018) Find in CUMINCAD Machine learning for architectural design: Practices and infrastructure. , International Journal of Architectural Computing, 16(2), pp. 123-143

100%; open Tseranidis, S., Brown, N.C. and Mueller, C.T. (2016) Find in CUMINCAD Data-driven approximation algorithms for rapid performance evaluation and optimization of civil structures , Automation in Construction, 72, pp. 279-293

100%; open Tseranidis, S. (2015) Find in CUMINCAD Approximation Algorithms for Rapid Evaluation and Optimization of Architectural and Civil Structures , Master's Thesis, Massachusetts Institute of Technology

last changed 2020/09/09 09:52
pick and add to favorite papersHOMELOGIN (you are user _anon_377406 from group guest) CUMINCAD Papers Powered by SciX Open Publishing Services 1.002