Identifying Driving Factors in Flood‐Damaging Processes Using Graphical Models

[1]  J. Barredo Normalised flood losses in Europe: 1970-2006 , 2009 .

[2]  H. Kreibich,et al.  Data Collection for a Better Understanding of What Causes Flood Damage–Experiences with Telephone Surveys , 2017 .

[3]  H. Kreibich,et al.  Assessment of damage caused by high groundwater inundation , 2008 .

[4]  Sarah E. Kienzler,et al.  Coping with Pluvial Floods by Private Households , 2016 .

[5]  Heidi Kreibich,et al.  A comparative survey of the impacts of extreme rainfall in two international case studies , 2017 .

[6]  Frank Scherbaum,et al.  Modeling the Joint Probability of Earthquake, Site, and Ground-Motion Parameters Using Bayesian Networks , 2011 .

[7]  J. Cain Planning improvements in natural resource management. Guidelines for using Bayesian networks to support the planning and management of development programmes in the water sector and beyond , 2001 .

[8]  Santiago Zazo,et al.  Assessment of Temporally Conditioned Runoff Fractions in Unregulated Rivers , 2018 .

[9]  Heidi Kreibich,et al.  New insights into flood warning reception and emergency response by affected parties , 2017 .

[10]  B. Merz,et al.  Flood damage and influencing factors: New insights from the August 2002 flood in Germany , 2005 .

[11]  Laura Uusitalo,et al.  Advantages and challenges of Bayesian networks in environmental modelling , 2007 .

[12]  Daniel Straub,et al.  Natural hazards risk assessment using Bayesian networks , 2005 .

[13]  Robert Castelo,et al.  On Inclusion-Driven Learning of Bayesian Networks , 2003, J. Mach. Learn. Res..

[14]  Zexuan Zhu,et al.  Markov blanket-embedded genetic algorithm for gene selection , 2007, Pattern Recognit..

[15]  Usama M. Fayyad,et al.  Multi-Interval Discretization of Continuous-Valued Attributes for Classification Learning , 1993, IJCAI.

[16]  A. Thieken,et al.  Damage assessment in Braunsbach 2016: data collection and analysis for an improved understanding of damaging processes during flash floods , 2017 .

[17]  B. Merz,et al.  Development and evaluation of FLEMOps - a new Flood Loss Estimation MOdel for the private sector , 2008 .

[18]  Bruno Merz,et al.  Insurability and Mitigation of Flood Losses in Private Households in Germany , 2006, Risk analysis : an official publication of the Society for Risk Analysis.

[19]  I. Kelman,et al.  An overview of flood actions on buildings , 2004 .

[20]  H. Kreibich,et al.  Flood Damage Modeling on the Basis of Urban Structure Mapping Using High-Resolution Remote Sensing Data , 2014 .

[21]  Bruno Merz,et al.  Review article "Assessment of economic flood damage" , 2010 .

[22]  Wolfgang Kron Überschwemmungsüberraschung: Sturzfluten und Überschwemmungen fernab von Gewässern , 2009 .

[23]  A. Thieken Contributions of Flood Insurance to Enhance Resilience–Findings from Germany , 2018 .

[24]  Heidi Kreibich,et al.  A Review of Flood Loss Models as Basis for Harmonization and Benchmarking , 2016, PloS one.

[25]  Frank Scherbaum,et al.  Bayesian networks for tsunami early warning , 2011 .

[26]  Heidi Kreibich,et al.  The flood of June 2013 in Germany: how much do we know about its impacts? , 2016 .

[27]  Heidi Kreibich,et al.  Coping with floods in the city of Dresden, Germany , 2009 .

[28]  Stefan Lüdtke,et al.  Regional and Temporal Transferability of Multivariable Flood Damage Models , 2018 .

[29]  H. Kreibich,et al.  Influence of flood frequency on residential building losses , 2010 .

[30]  Bruno Merz,et al.  The extreme flood in June 2013 in Germany , 2014 .

[31]  A. Thieken,et al.  Adaptability and transferability of flood loss functions in residential areas , 2013 .

[32]  Dimitris Margaritis,et al.  Speculative Markov blanket discovery for optimal feature selection , 2005, Fifth IEEE International Conference on Data Mining (ICDM'05).

[33]  Rafael Rumí,et al.  Bayesian networks in environmental modelling , 2011, Environ. Model. Softw..

[34]  B. Merz,et al.  Coping with floods: preparedness, response and recovery of flood-affected residents in Germany in 2002 , 2007 .

[35]  Carsten Riggelsen,et al.  Learning Bayesian Networks: A MAP Criterion for Joint Selection of Model Structure and Parameter , 2008, 2008 Eighth IEEE International Conference on Data Mining.

[36]  Wolfgang Kron,et al.  How to deal properly with a natural catastrophe database – analysis of flood losses , 2012 .

[37]  Anders L. Madsen,et al.  The Hugin Tool for Learning Bayesian Networks , 2003, ECSQARU.

[38]  Bruno Merz,et al.  Multi-variate flood damage assessment: a tree-based data-mining approach , 2013 .

[39]  Pedro Larrañaga,et al.  A review of feature selection techniques in bioinformatics , 2007, Bioinform..

[40]  Kashif Javed,et al.  A two-stage Markov blanket based feature selection algorithm for text classification , 2015, Neurocomputing.

[41]  Sarah E. Kienzler,et al.  Review of the flood risk management system in Germany after the major flood in 2013 , 2016 .

[42]  Bruno Merz,et al.  What made the June 2013 flood in Germany an exceptional event? A hydro-meteorological evaluation , 2014 .

[43]  Frank Scherbaum,et al.  Bayesian network learning for natural hazard analyses , 2014 .

[44]  Bruno Merz,et al.  How useful are complex flood damage models? , 2014 .

[45]  B. Merz,et al.  Estimation uncertainty of direct monetary flood damage to buildings , 2004 .