MATEC Web Conf.
Volume 67, 2016International Symposium on Materials Application and Engineering (SMAE 2016)
|Number of page(s)||5|
|Section||Chapter 7 Materials Application and Engineering|
|Published online||29 July 2016|
- Asaoka A, Observational procedure of settlement prediction. Soils & Foundations, 1978, 18(4): 87–101. [Google Scholar]
- Qian YL, Ding Y, Forecasting settlement of roadbed and its engineering application. Journal of Yangzhou University (Natural Science Edition), 2001, 4(2): 75–78. [Google Scholar]
- Chen XD, Xia J. Xu Q, Differential hydrological grey model (DHGM) with self-memory function and its application to flood forecasting. Science China Technological Sciences, 2009, 39 (2), 341–350 [Google Scholar]
- Cortes C., Vapnik V., Support vector network. Mach. Learn, 1995, 20, 273–297. [Google Scholar]
- Cherkassky V., Mulier F., Learning from Data: Concepts, Theory and Methods. Wiley, New York, 1998. [Google Scholar]
- Dibike YB, Velikov S, Solomatine D, Abbott MB, Model induction with support vector machines: introduction and applications. J Comput Civ Eng ASCE, 2001, 15(3):208–16. [CrossRef] [Google Scholar]
- Cristianini N, Shaw-Taylor J. An introduction to support vector machines and other kernel-based learning methods. Cambridge: Cambridge University Press, 2000. [Google Scholar]
- Samui P. Support vector machine applied to settlement of shallow foundations on cohesionless soils. Comput Geotech, 2008, 35:419–27. [CrossRef] [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.