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 acadia18_196
authors Zhang, Yan; Grignard; Aubuchon, Alexander; Lyons, Keven; Larson, Kent
year 2018
title Machine Learning for Real-time Urban Metrics and Design Recommendations
source ACADIA // 2018: Recalibration. On imprecisionand infidelity. [Proceedings of the 38th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-17729-7] Mexico City, Mexico 18-20 October, 2018, pp. 196-205
summary Cities are growing, becoming more complex, and changing rapidly. Currently, community engagement for urban decision-making is often ineffective, uninformed, and only occurs in projects’ later stages. To facilitate a more collaborative and evidence-based urban decision- making process for both experts and non-experts, real-time feedback and optimized suggestions are essential. However, most of the current tools for urban planning are neither capable of performing complex simulations in real time nor of providing guidance for better urban performance.

CityMatrix was introduced to address these challenges. Machine learning techniques were applied to achieve real-time prediction of multiple urban simulations, and thousands of city configurations were simulated. The simulation results were used to train a convolutional neural network (CNN) to predict the traffic and solar performance of unseen city configurations. The prediction with the CNN is thousands of times faster than the original simulations and maintains a high-quality representation of the results. This machine learning approach was applied as a versatile, quick, accurate, and computationally efficient method not only for real-time feedback, but also for optimized design recommendations. Users involved in the evaluation of this project had a better understanding of the embodied trade-offs of the city and achieved their goals in an efficient manner.

keywords full paper, optimization, collaboration, urban design & analysis, ai & machine learning
series ACADIA
type paper
email ryanz@mit.edu
full text file.pdf (6,819,463 bytes)
references Content-type: text/plain
Details Citation Select
100%; open Abadi, Martín, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Greg S Corrado, Andy Davis, Jeffrey Dean, Matthieu Devin, et al. (2016) Find in CUMINCAD Tensorflow: Large-Scale Machine Learning on Heterogeneous Distributed Systems , arXiv preprint arXiv:1603.04467

100%; open Alonso, Luis, Yan Zhang, Arnaud Grignard, Ariel Noyman, Yasushi Sakai, Markus Elkatsha, Ronan Doorley, and Kent Larson (2018) Find in CUMINCAD Data-Driven, Evidence-Based Simulation of Urban Dynamics: Use Case Volpe , Unifying Themes in Complex Systems IX: Proceedings of the Ninth International Conference on Complex Systems, 253–61. Cham, Switzerland: Springer

100%; open Browne, C.B., E. Powley, D. Whitehouse, S.M. Lucas, P.I. Cowling, P. Rohlfshagen, S. Tavener, D. Perez, S. Samothrakis, and S. Colton (2012) Find in CUMINCAD A Survey of Monte Carlo Tree Search Methods , IEEE Transactions on Computational Intelligence and AI in Games 4 (1): 1-43

100%; open Grignard, Arnaud, and Alexis Drogoul (2017) Find in CUMINCAD Agent-Based Visualization: A Real-Time Visualization Tool Applied Both to Data and Simulation Outputs , The Workshops of the Thirty-First AAAI Conference on Artificial Intelligence: Human-Machine Collaborative Learning, 670–5. San Francisco: AAAI

100%; open Grignard, Arnaud, Núria Maci?, Luis Alonso Pastor, Ariel Noyman, Yan Zhang, and Kent Larson (2018) Find in CUMINCAD CityScope Andorra: A Multi-level Interactive and Tangible Agent-based Visualization , Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems, 1939–40. Stockholm, Sweden: AAMAS

100%; open Grignard, Arnaud, Patrick Taillandier, Benoit Gaudou, Duc An Vo, Nghi Quang Huynh, and Alexis Drogoul (2013) Find in CUMINCAD GAMA 1.6: Advancing the Art of Complex Agent-Based Modeling and Simulation , PRIMA 13: International Conference on Principles and Practice of Multi-Agent Systems, 117–31. Berlin: Springer

100%; open Grimm, Nancy B., S.H. Faeth, N.E. Golubiewski, C.L. Redman, J. Wu, X. Bai, and J.M. Briggs (2008) Find in CUMINCAD Global Change and the Ecology of Cities , Science 319 (5864): 756–60

100%; open Krizhevsky, Alex, Ilya Sutskever, and Geoffrey E Hinton (2012) Find in CUMINCAD Imagenet Classification with Deep Convolutional Neural Networks , Proceedings of the 25th International Conference on Neural Information Processing Systems 1097–1105. Lake Tahoe, NV: NIPS

100%; open Kröner, Andreas, P. Holl, W. Marquardt, and E.D. Gilles (1990) Find in CUMINCAD DIVA: An Open Architecture for Dynamic Simulation , Computers & Chemical Engineering 14 (11): 1289–95

100%; open Midgley, James, and Anthony Hall (1986) Find in CUMINCAD Community Participation, Social Development and the State , London: Routledge

100%; open Niepert, Mathias, Mohamed Ahmed, and Konstantin Kutzkov (2016) Find in CUMINCAD Learning Convolutional Neural Networks for Graphs , Proceedings of Machine Learning Research 48: 2014–23

100%; open Rajpurkar, Pranav, Awni Y Hannun, Masoumeh Haghpanahi, Codie Bourn, and Andrew Y Ng. (2017) Find in CUMINCAD Cardiologist-Level Arrhythmia Detection with Convolutional Neural Networks , arXiv preprint arXiv:1707.01836

100%; open Silver, David, Aja Huang, Chris J Maddison, Arthur Guez, Laurent Sifre, George Van Den Driessche, Julian Schrittwieser, Ioannis Antonoglou, Veda Panneershelvam, Marc Lanctot, et al. (2016) Find in CUMINCAD Mastering the Game of Go with Deep Neural Networks and Tree Search , Nature 529 (7587): 484–89

100%; open Underkoffler, John, and Hiroshi Ishii (1999) Find in CUMINCAD Urp: A Luminous-Tangible Workbench for Urban Planning and Design , Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 386–393. Pittsburgh, PA: CHI

100%; open Zhang, Yan, and Kent Larson (2018) Find in CUMINCAD CityScope: Application of Tangible Interface, Augmented Reality, and Artificial Intelligence in the Urban Decision Support System , Time + Architecture 2018 (01): 44–49

100%; open Zhang, Yan (2017) Find in CUMINCAD CityMatrix: an urban decision support system augmented by artificial intelligence , Master’s thesis, Massachusetts Institute of Technology

last changed 2019/01/07 11:21
pick and add to favorite papersHOMELOGIN (you are user _anon_229210 from group guest) CUMINCAD Papers Powered by SciX Open Publishing Services 1.002