Combination four different ensemble algorithms with the generalized linear model (GLM) for predictin...
Combination four different ensemble algorithms with the generalized linear model (GLM) for predicting forest fire susceptibility
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Publisher
Abingdon: Taylor & Francis
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Language
English
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Abingdon: Taylor & Francis
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Contents
In this study, the generalized linear model (GLM) and four ensemble methods (partial least squares (PLS), boosting, bagging, and Bayesian) were applied to predict forest fire hazard in the Chalus Rood watershed in the Mazandaran Province, Iran. Data from 108 historical forest fire events collected through field surveys were applied as the basis of...
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Full title
Combination four different ensemble algorithms with the generalized linear model (GLM) for predicting forest fire susceptibility
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Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_f66ffa9595144ba69c390b5ce224fb48
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_f66ffa9595144ba69c390b5ce224fb48
Other Identifiers
ISSN
1947-5705
E-ISSN
1947-5713
DOI
10.1080/19475705.2023.2206512
