Novel forecasting approaches using combination of machine learning and statistical models for flood susceptibility mapping

Clicks: 320
ID: 261252
2018
Free PDF
Article Quality & Performance Metrics
Overall Quality Improving Quality
0.0 /100
Combines engagement data with AI-assessed academic quality
AI Quality Assessment
Not analyzed
Abstract
In this research, eight individual machine learning and statistical models are implemented and compared, and based on their results, seven ensemble models for flood susceptibility assessment are introduced. The individual models included artificial neural networks, classification and regression tree …
Reference Key
h2018journalnovel Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Shafizadeh-Moghadam H;Valavi R;Shahabi H;Chapi K;Shirzadi A;;
Journal Journal of environmental management
Year 2018
DOI
DOI not found
URL
https://www.ncbi.nlm.nih.gov/pubmed/29579536
Keywords
iran National Center for Biotechnology Information NCBI NLM MEDLINE pubmed abstract nih national institutes of health national library of medicine models statistical Forecasting machine learning* roc curve ataollah shirzadi floods* pmid:29579536 doi:10.1016/j.jenvman.2018.03.089 hossein shafizadeh-moghadam roozbeh valavi

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.