Estimation of seismic building structural types using multi-sensor remote sensing and machine learning techniques
作者： Christian Geiß , Patrick Aravena Pelizari , Mattia Marconcini , Wayan Sengara , Mark Edwards
DOI: 10.1016/J.ISPRSJPRS.2014.07.016
关键词:
摘要: Detailed information about seismic building structural types (SBSTs) is crucial for accurate earthquake vulnerability and risk modeling as it reflects the main load-bearing structures of buildings and, thus, the behavior under seismic load. However, for numerous urban areas in earthquake prone regions this information is mostly outdated, unavailable, or simply not existent. To this purpose, we present an effective approach to estimate SBSTs by combining scarce in situ observations, multi-sensor remote sensing data and machine learning …
harvard.edu
core.ac.uk
elsevier.com
sci-hub.se 参考文章(65)
Gustau Camps-Valls, Lorenzo Bruzzone, None, Kernel methods for remote sensing data analysis Wiley. ,(2009) , 10.1002/9780470748992
Paula K. Dunbar, Roger G. Bilham, Melinda J. Laituri, Earthquake Loss Estimation for India Based on Macroeconomic Indicators Springer Netherlands. pp. 163- 180 ,(2003) , 10.1007/978-94-010-0167-0_13
Matthew Wiener, Andy Liaw, Classification and Regression by randomForest ,(2007)
M. Hall, Correlation-based Feature Selection for Machine Learning PhD Thesis, Waikato Univer-sity. ,(1998)
Marko Robnik-Šikonja, Igor Kononenko, Theoretical and Empirical Analysis of ReliefF and RReliefF Machine Learning. ,vol. 53, pp. 23- 69 ,(2003) , 10.1023/A:1025667309714
Chih-Jen Lin, Chih-Wei Hsu, A Comparison of Methods for Multi-class Support Vector Machines ,(2015)
Keki B. Irani, Usama M. Fayyad, Multi-Interval Discretization of Continuous-Valued Attributes for Classification Learning international joint conference on artificial intelligence. ,vol. 2, pp. 1022- 1027 ,(1993)
Richard A Olshen, Charles J Stone, Leo Breiman, Jerome H Friedman, Classification and regression trees ,(1983)
Robin Genuer, Christine Tuleau, Jean-Michel Poggi, Random Forests: some methodological insights arXiv: Machine Learning. ,(2008)
Igor Kononenko, Estimating attributes: analysis and extensions of RELIEF european conference on machine learning. pp. 171- 182 ,(1994) , 10.1007/3-540-57868-4_57