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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	Haeusler M. H., Butler A., Gardner N., Sepasgozar S. and Pan S. (2021) Wasted ... Again - Or how to understand waste asa data problem and aiming to address the reduction of waste as a computational challenge , A. Globa, J. van Ameijde,A. Fingrut, N. Kim, T.T.S. Lo (eds.), PROJECTIONS - Proceedings of the 26th CAADRIA Conference - Volume 1, The Chinese University of Hong Kong and Online, Hong Kong, 29 March - 1 April 2021, pp. 371-380

	Haeusler, M. H., Butler, A., Gardner, N., Sepasgozar, S., and Pan, S. (2021) Wasted ... Again - Or how to understand waste as a data problem and aiming to address the reduction of waste as a computational challenge , CAADRIA, 1(26th), 371-380

	Haeusler, M.H., Butler, A., Gardner, N., Sepasgozar, S. & Pan, S. (2021) Wasted .. again: Or how to understand waste as a data problem and aiming to address the reduction of waste as a computational challenge , Proceedings of CAADRIA 2021, 26th International Conference of the Association for Computer-Aided Architectural Design Research in Asia, (pp. 371-380)

	Haeusler, M.H., Butler, A., Gardner, N., Sepasgozar, S. & Pan, S. (2021) Wasted .. again: Or how to understand waste as a data problem and aiming to address the reduction of waste as a computational challenge , Proceedings of CAADRIA 2021, 26th International Conference of the Association for Computer-Aided Architectural Design Research in Asia, (pp. 371-380)

	Haeusler, M.H., Butler, A., Gardner, N., Sepasgozar, S., & Pan, S. (2021) Wasted again: Or how to understand waste as a data problem and aiming to address the reduction of waste as a computational challenge , Proceedings of 26th International Conference of the Association for Computer-Aided Architectural Design Research in Asia, CAADRIA (pp. 371 - 380)

	Haeusler, MH, Gardner, N, Butler, A, Sepasgozar, S and Pan, S (2021) Wasted ... Again - Or how to understand waste as a data problem and aiming to address the reduction of waste as a computational challenge , CAADRIA 2021, Hong Kong, pp. 371-380

	Haining, R. P., & Haining, R. (2003) Spatial Data Analysis: Theory and Practice , Cambridge university press. http://dx.doi.org/1.117/CBO978511754944

	Haining, R. (1995) Spatial analysis and GIS , Fotheringham, A.S. and P. Rogerson (eds.), Designing spatial data analysis modules for Geographical Information Systems. Taylor & Francis, London, pp. 45-64

	Hair, J F., Anderson, R E., Tatham, R.L. and Black, W.C. (1995) Conjoint Analysis in Multivariate Data Analysis , Prentice Hall, Englewood Cliffs NJ, pp. 556-599

	Hair, J. F., Tatham, R. L., y Anderson, R. E. (2006) Multivariate data analysis , Upper Saddle River, N.J: Prentice Hall PTR

	Hair, J.F., Anderson, R.E., Tatham. R.L. and Black, W.C. (1995) Conjoint Analysis, in Multivariate Data Analysis , Prentice Hall, Englewood Cliffs N, pp. 556-599

	Hair, J.F., R.E. Anderson, R.L. Tatham and W.C. Black (1995) Conjoint analysis, in Multivariate data Analysis , Prentice Hall, Englewood Cliffs NJ, pp. 556-599

	Halevy A., Norvig P. and Pereira F. (2009) The unreasonable effectiveness of data , IEEE Intell Syst; 24(2): 8–12

	Halevy, Alon and Norvig, Peter (2009) The Unreasonable Effectiveness of Data , IEEE Computer Society

	Hall, D.L., Llinas, J. (1997) Introduction to Multisensor Data Fusion , Proceedings of the IEEE, 85(1), pp. 6–23

	Hall, M, et al. (2009) The WEKA Data Mining Software: An Update , SIGKDD Explorations

	Halpern, O. (2015) Beautiful data: A history of vision and reason since 1945 , Duke University Press

	Han KK and Golparvar-Fard M (2014) Potential of big visual data and building information modeling for construction performance analytics: n exploratory study , Automat Construct 2017; 73: 184–198

	Han, J and Kamber, M (2001) Data Mining: Concepts and Techniques , Morgan Kaufmann Publishers, San Francisco, USA

	Han, J, Kamber, M and Pei, J (2012) 10 - Cluster Analysis: Basic Concepts and Methods , Han, J, Kamber, M and Pei, J (eds), Data Mining (Third Edition), Morgan Kaufmann, Boston, pp. 443-495

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