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  • The paper presented herein compares and discusses the use of bivariate, multivariate and soft computing techniques for collapse susceptibility modelling. Conditional probability (CP), logistic regression (LR) and artificial neural networks (ANN) models representing the bivariate, multivariate and soft computing techniques were used in GIS based collapse susceptibility mapping in an area from Sivas basin (Turkey). Collapse-related factors, directly or indirectly related to the causes of collapse occurrence, such as distance from faults, slope angle and aspect, topographical elevation, distance from drainage, topographic wetness index (TWI), stream power index (SPI), Normalized Difference Vegetation Index (NDVI) by means of vegetation cover, distance from roads and settlements were used in the collapse susceptibility analyses. In the last stage of the analyses, collapse susceptibility maps were produced from the models, and they were then compared by means of their validations. However, Area Under Curve (AUC) values obtained from all three models showed that the map obtained from soft computing (ANN) model looks like more accurate than the other models, accuracies of all three models can be evaluated relatively similar. The results also showed that the conditional probability is an essential method in preparation of collapse susceptibility map and highly compatible with GIS operating features.
  • The paper presented herein compares and discusses the use of bivariate, multivariate and soft computing techniques for collapse susceptibility modelling. Conditional probability (CP), logistic regression (LR) and artificial neural networks (ANN) models representing the bivariate, multivariate and soft computing techniques were used in GIS based collapse susceptibility mapping in an area from Sivas basin (Turkey). Collapse-related factors, directly or indirectly related to the causes of collapse occurrence, such as distance from faults, slope angle and aspect, topographical elevation, distance from drainage, topographic wetness index (TWI), stream power index (SPI), Normalized Difference Vegetation Index (NDVI) by means of vegetation cover, distance from roads and settlements were used in the collapse susceptibility analyses. In the last stage of the analyses, collapse susceptibility maps were produced from the models, and they were then compared by means of their validations. However, Area Under Curve (AUC) values obtained from all three models showed that the map obtained from soft computing (ANN) model looks like more accurate than the other models, accuracies of all three models can be evaluated relatively similar. The results also showed that the conditional probability is an essential method in preparation of collapse susceptibility map and highly compatible with GIS operating features. (en)
Title
  • An assessment on the use of bivariate, multivariate and soft computing techniques for collapse susceptibility in GIS environ
  • An assessment on the use of bivariate, multivariate and soft computing techniques for collapse susceptibility in GIS environ (en)
skos:prefLabel
  • An assessment on the use of bivariate, multivariate and soft computing techniques for collapse susceptibility in GIS environ
  • An assessment on the use of bivariate, multivariate and soft computing techniques for collapse susceptibility in GIS environ (en)
skos:notation
  • RIV/61989100:27350/13:86088911!RIV14-MSM-27350___
http://linked.open...avai/predkladatel
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • V
http://linked.open...iv/cisloPeriodika
  • APR 2013
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 60313
http://linked.open...ai/riv/idVysledku
  • RIV/61989100:27350/13:86088911
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • soft computing (artificial neural networks); multivariate (logistic regression); bivariate (conditional probability); GIS; gypsum; Collapse susceptibility map (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...odStatuVydavatele
  • US - Spojené státy americké
http://linked.open...ontrolniKodProRIV
  • [B138B0533BF2]
http://linked.open...i/riv/nazevZdroje
  • Journal of Earth System Science
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...UplatneniVysledku
http://linked.open...v/svazekPeriodika
  • 122
http://linked.open...iv/tvurceVysledku
  • Marschalko, Marian
  • Yilmaz, Isik
  • Bednarik, Martin
http://linked.open...ain/vavai/riv/wos
  • 000317606500008
issn
  • 0253-4126
number of pages
http://bibframe.org/vocab/doi
  • 10.1007/s12040-013-0281-3
http://localhost/t...ganizacniJednotka
  • 27350
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