Comparative Evaluation of ANN- and SVM-Time Series Models for Predicting Freshwater-Saltwater Interf...
Comparative Evaluation of ANN- and SVM-Time Series Models for Predicting Freshwater-Saltwater Interface Fluctuations
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Basel: MDPI AG
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Language
English
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Basel: MDPI AG
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Contents
Time series models based on an artificial neural network (ANN) and support vector machine (SVM) were designed to predict the temporal variation of the upper and lower freshwater-saltwater interface level (FSL) at a groundwater observatory on Jeju Island, South Korea. Input variables included past measurement data of tide level (T), rainfall (R), gr...
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Full title
Comparative Evaluation of ANN- and SVM-Time Series Models for Predicting Freshwater-Saltwater Interface Fluctuations
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TN_cdi_proquest_journals_1910586083
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_1910586083
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ISSN
2073-4441
E-ISSN
2073-4441
DOI
10.3390/w9050323
