Using the rotation and random forest models of ensemble learning to predict landslide susceptibility
نویسندگان
چکیده
منابع مشابه
An Ensemble Model for Co-Seismic Landslide Susceptibility Using GIS and Random Forest Method
The Mw 7.8 Gorkha earthquake of 25 April 2015 triggered thousands of landslides in the central part of the Nepal Himalayas. The main goal of this study was to generate an ensemble-based map of co-seismic landslide susceptibility in Sindhupalchowk District using model comparison and combination strands. A total of 2194 co-seismic landslides were identified and were randomly split into 1536 (~70%...
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The aim of current research is to assess of landslide susceptibility in the Khalkhal Township, southern Ardabil using an ensemble and new method namely Bayesian and logistic regression (BT-LR) models. At first, landslide inventory map was prepared and then effective factors on landslide occurrence were identified. These factors are slope degree, plan curvature, slope aspect, elevation, landuse,...
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with the growth of more humanistic approaches towards teaching foreign languages, more emphasis has been put on learners’ feelings, emotions and individual differences. one of the issues in teaching and learning english as a foreign language is demotivation. the purpose of this study was to investigate the relationship between the components of language learning strategies, optimism, duration o...
15 صفحه اولRandom Forest Models To Predict Aqueous Solubility
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Landslide susceptibility zonation mapping is necessary in urban and rural development planning. So far different methods are presented for Landslide susceptibility zonation. In this study, using statistical method of Frequency ratio and Analytical Hierarchy Process (AHP) based on paired comparison and intervention based such as slope, aspect, altitude, geology, land use, Normalized vegetatio...
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ژورنال
عنوان ژورنال: Geomatics, Natural Hazards and Risk
سال: 2020
ISSN: 1947-5705,1947-5713
DOI: 10.1080/19475705.2020.1803421