Assessment of Advanced Artificial Intelligence Techniques for Streamflow Forecasting in Jhelum River...
Assessment of Advanced Artificial Intelligence Techniques for Streamflow Forecasting in Jhelum River Basin
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Publisher
Islamabad: Pakistan Agricultural Research Council
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Language
English
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Publisher
Islamabad: Pakistan Agricultural Research Council
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Contents
Streamflow forecasting is a crucial hydrological variable. In the current study, the Artificial Intelligence (AI) based techniques: TB (Tree Boost), DTF Decision Tree Forest, SDT Single Decision Tree and conventional Multilayer Perceptron Neural Networks (MLPNN) are used for predicting streamflow of Jhelum River basin. The dataset was divided into...
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Full title
Assessment of Advanced Artificial Intelligence Techniques for Streamflow Forecasting in Jhelum River Basin
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TN_cdi_proquest_journals_2607839619
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2607839619
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ISSN
0251-0480
E-ISSN
0251-0480,2227-8311
DOI
10.17582/journal.pjar/2021/34.3.580.598
