Cumincad : CUMINCAD References : Search Results

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

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	Pan W, Sun Y, Turrin M, et al (2020) Design exploration of quantitative performance and geometry typology for indoor arena based on self-organizing map and multi-layered perceptron neural network , Autom Constr 2020; 114: 103163.

	SASS, L. (2004) Design for self assembly of building components using rapid prototyping , Architecture in the network society. 22nd eCAADe conference proceedings. Copenhagen, Denmark. pp. 95-104

	Sass, L. (2004) Design for Self Assembly of Building Components using Rapid Prototyping , Architecture in the Network Society, 22nd eCAADe Conference Proceedings Copenhagen (Denmark) 15-18 September 2004

	Sass, L. (2004) Design for Self Assembly of Building Components using Rapid Prototyping , eCAADe22: Architecture in the Network Society, Copenhagen, Denmark

	Sass, Lawrence (2004) Design for Self Assembly of Building Components using Rapid Prototyping , Architecture in the Network Society [eCAADe 2004 proceedings], eds. B. Rüdiger, B. Tournay, and H. Orbak: 95-104. Copenhagen: eCAADe

	Yang, Y.-F., Sun, M. (2021) A Novel Deep Learning Architecture for Global Defect Classification: Self-Proliferating Neural Network (SPNet) , 32nd Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC)

	A Bidgoli. and P. Veloso (2018) DeepCloud: The Application of a Data-Driven, Generative Model in Design , ACADIA 18: Recalibration, Proceedings of the 38th Annual Conference of the Association for Computer Aided Design in Architecture. 176–85

	A. Gandia, S. Parascho, R. Rust, G. Casas, F. Gramazio, and M. Kohler (2019) Towards Automatic Path Planning for Robotically Assembled Spatial Structures , ROBARCH 2018; Robotic Fabricationin Architecture, Art and Design 2018, Cham: Springer

	A. Groenewolt, T. Schwinn, L. Nguyen, and A. Menges (2018) An Interactive Agent-Based Framework for Materialization-Informed Architectural Design , Swarm Intelligence 12 (2): 155–86

	A. M. Salet, T (2018) Design of a 3D printed concrete bridge by testing , Virtual and Physical Prototyping, 13, pp. 222-236

	A. M. Salet, Theo, Y. Ahmeda, Zeeshan, P. Bos, Freek and L. M. Laaglandb, Hans (2018) Design of a 3D printed concrete bridge by testing , Virtual and Physical Prototyping, 13(3), pp. 222-236

	A. Nagabandi, I. Clavera, S. Liu, R.S. Fearing, P. Abbeel, S. Levine, and C. Finn (2018) Learning to Adapt in Dynamic, Real-World Environments Through Meta-Reinforcement Learning , ICLR 2019 Conference Paper, arXiv:1803.11347

	A. Paul., D.P. Mukherjee., P. Das., A. Gangopadhyay., A.R. Chintha., & S. Kundu. (2018) Improved Random Forest for Classification , IEEE Transactions on Image Processing, 27 (8). Available at: https://doi.org/1.119/TIP.218.283483.

	A. Thoma, A. Adel, M. Helmreich, T. Wehrle, F. Gramazio, and M. Kohler (2019) Robotic Fabrication of Bespoke Timber Frame Modules , Robotic Fabrication in Architecture, Art and Design (ROBARCH) 2018. Cham: Springer. 447–458

	A.B. Hernández, R.D. Brumbaugh, P. Frederick, et al (2018) Restoring the eastern oyster: how much progress has been made in 53 years? , Frontiers in Ecology and the Environment 16 (8): 463–471

	ABAB, . (2018) BIM Process Consistency: Towards a Common Framework for Digital Design, Construction and Operation , Australasian BIM Advisory Board

	Abbasabadi, N. and Ashayeri, M. (2019) Urban energy use modelling methods and tools: A review and an outlook , Building and Environment, 161, 106270. https://doi.org/10.1016/j.buildenv.2019.106270Alhamwi, A., Medjroubi, W., Vogt, T. and Agert, C. (2017). GIS-based urban energy systems models and tools: Introducing a model for the optimisation of flexibilisation technologies in urban areas. Applied Energy, 191, 1-9. https://doi.org/10.1016/j.apenergy.2017.01.048Chen, Y. and Hong, T. (2018). Impacts of building geometry modelling methods on the simulation results of urban building energy models. Applied Energy, 215, 717-735. https://doi.org/10.1016/j.apenergy.2018.02.073Chen, Y., Hong, T., Luo, X. and Hooper, B. (2019). Development of city buildings dataset for urban building energy modelling. Energy and Buildings, 183, 252-265. https://doi.org/10.1016/j.enbuild.2018.11.008Davila, C.C., Reinhart, C.F., and Bemis, J.L. (2016). Modelling Boston: A workflow for the efficient generation and maintenance of urban building energy models from existing geospatial datasets. Energy, 117, 237-250. https://doi.org/10.1016/j.energy.2016.10.057Dogan, T. and Reinhart, C. (2017). Shoeboxer: An algorithm for abstracted rapid multi-zone urban building energy model generation and simulation. Energy and Buildings, 140, 140-153. https://doi.org/10.1016/j.enbuild.2017.01.030EC. (2021). 2030 Climate Target Plan. European Commission. Retrieved June 1, 2021, from https://ec.europa.eu/clima/eu-action/european-green-deal/2030-climate-target-plan_en

	Abdalla MM, Oliveira LGL, Azevedo CEF, et al (2018) Quality in qualitative organizational research: types of triangulation as a methodological alternative , RAEP 2018; 19(1): 66–98.

	Abdelhameed, W. (2018) BIM in architecture curriculum: a case study , Architectural Science Review, 61(6), pp. 480-491.

	Abdelmohsen S, Massoud P, El-Dabaa R, et al. (2018) A computational method for tracking the hygroscopic motion of wood to develop adaptive architectural skins , Computing for a Better Tomorrow - Proceedings of the 36th ECAADe Conference - Volume 2 (eds A Kepczynska-Walczak and S Bialkowski), pp. 253–62. Lodz, Poland: Lodz University of Technology

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