Novel ensemble machine learning models in flood susceptibility mapping-Reference-Cited by-同舟云学术

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Novel ensemble machine learning models in flood susceptibility mapping

Published:2021-03-08 Issue: Volume: Page:1-23
ISSN:1010-6049
Container-title:Geocarto International
language:en
Short-container-title:Geocarto International

Author:

Prasad Pankaj¹²^ORCID,Loveson Victor Joseph¹,Das Bappa³^ORCID,Kotha Mahender²

Affiliation:

1. Geological Oceanography Division, CSIR - National Institute of Oceanography, Dona Paula, Goa, India

2. School of Earth, Ocean and Atmospheric Sciences, Goa University, Taleigao, Goa, India

3. Natural Resource Management Section, ICAR-Central Coastal Agricultural Research Institute, Old Goa, Goa, India

Publisher

Informa UK Limited

Subject

Water Science and Technology,Geography, Planning and Development

Link

https://www.tandfonline.com/doi/pdf/10.1080/10106049.2021.1892209

Reference91 articles.

1. Flood susceptibility mapping and assessment using a novel deep learning model combining multilayer perceptron and autoencoder neural networks

2. Flood susceptibility assessment using integration of adaptive network-based fuzzy inference system (ANFIS) and biogeography-based optimization (BBO) and BAT algorithms (BA)

3. Mapping flood susceptibility in an arid region of southern Iraq using ensemble machine learning classifiers: a comparative study

4. adabag: AnRPackage for Classification with Boosting and Bagging

5. Tree-based ensemble models for predicting the ICU transfer of stroke in-patients

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