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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	Bennett, KP and Demiriz, A (1999) Semi-Supervised Support Vector Machines , Advances in Neural Information Processing Systems, 11, pp. 368-374

	Bennett, KP and Demiriz, A (1999) Semi-Supervised Support Vector Machines , Advances in Neural Information Processing Systems, 11, pp 368-374

	Joachims, T (1999) Making large-scale SVM learning practical BT - Advances in Kernel Methods - Support Vector Learning , MIT-Press

	Joachims, T (1999) Making Large-Scale SVM Learning Practical BT - Advances in Kernel Methods - Support Vector Learning , MIT-Press

	Berges, J.C. (1998) A Tutorial on Support Vector Machines for Pattern Recognition , Data Mining and Knowledge Discovery, 2(2): 21-167

	Chen JL, Liu HB, Wu W, et al (2011) Estimation of monthly solar radiation from measured temperatures using support vector machines–a case study , Renew Energy 2011; 36: 413–420

	Choubin, B., Moradi, E., Golshan, M., Adamowski, J., Sajedi-Hosseini, F., & Mosavi, A. (2019) An ensemble prediction of flood susceptibility using multivariate discriminant analysis, classification and regression trees, and support vector machines , The Science of the total environment, 2019-02, Vol.651 (Pt 2), p.2087-2096"

	Dong, B, Cao, C and Lee, SE (2005) Applying support vector machines to predict building energy consumption in tropical region , Energy and Buildings, 37(5), pp. 545-553

	Dong, B., Cao, C., & Lee, S.E. (2005) Applying Support Vector Machines to Predict Building Energy Consumption in Tropical Region , Energy and Buildings, 37(5), 545-553. Available at: https://doi.org/1.116/j.enbuild.24.9.9.

	Joachims, T. (1998) Text Categorization with Support Vector Machines: Learning with Many Relevant Features , Lecture Notes in Computer Science, 1398, Springer-Verlag

	Kecman, V. (2001) Learning and Soft Computing. Support Vector Machines , Neural Networks and Fuzzy Logic Models. The MIT Press, London

	Koo, B., La, S., Cho, NW. and Yu, Y. (2019) Using support vector machines to classify building elements for checking the semantic integrity of building information models , Automation in Construction, 98, 183-194

	Ma, Z., Ye, C., Li, H., & Ma, W. (2018) Applying Support Vector Machines to Predict Building Energy Consumption in China , Energy Procedia, 152, 78-786. Available at: https://doi.org/1.116/j.egypro.218.9.245

	Schölkopf B. and Smola A.J. (2001) Learning with kernels: support vector machines, regularization, optimization, and beyond (Adaptive computation and machine learning) , Cambridge, MA: The MIT Press

	Schölkopf, B., and Smola, A. (2002) Learning with kernels: Support vector machines, regularization, optimization, and beyond , The MIT Press

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

	(1999) Towards a generative system for intelligent design support , Paper presented at the Proceedings of the 4th CAADRIA Conference

	Arentze, T.A. (1999) A Spatial Decision Support System for the Planning of Retail and Service Facilities , (Ph.D. thesis) Eindhoven University of Technology, The Netherlands

	Arentze, T.A. (1999) A Spatial Decision Support System for the Planning of Retail and Service Facilities , Ph.D. thesis, Department of Architecture, Building and Planning, Technische Universiteit Eindhoven, Eindhoven

	Ball, L.J. and Lambell, N.J. (et al.) (1999) Representing design rationale to support innovative design re-use: a minimalist approach , 4th Design Thinking Research Symposium on Design Representation, Cambridge, MA, MIT

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