Show simple item record

dc.contributor.authorDanandeh Mehr, Ali
dc.contributor.authorNourani, Vahid
dc.contributor.authorKarimi Khosrowshahi, Vahid
dc.contributor.authorGhorbani, Moahmmad Ali
dc.identifier.citationDanandeh Mehr, A., Nourani, V., Karimi Khosrowshahi V., & Ghorbani, M. A. (2019). A hybrid support vector regression firefly model for monthly rainfall forecasting, International Journal of Environmental Science and Technology, 16(1), 335–346.en_US
dc.description.abstractLong-term prediction of rainfalls is one of the most challenging tasks in stochastic hydrology owing to the highly random characteristics of rainfall events. In this paper, a novel approach is adopted to develop a hybrid regression model for 1-month-ahead rainfall forecasting at two rain gauge locations (namely: Tabriz and Urmia stations), in northwest Iran. The approach is based on the integration of support vector regression (SVR) and firefly algorithm (FFA) that results in truthful rainfall forecasts. The proposed hybrid model was trained and validated using weak stationary state of monthly rainfall data obtained from the gauges. The efficiency results of the model were also cross-validated with those of stand-alone SVR- and genetic programming-based forecasting models developed as the benchmarks in this study. For both rain gauge locations, the results showed that the hybrid model significantly outperforms the benchmarks. With respect to the average efficiency results at the gauge locations, the FFA-induced improvement in the SVR forecasts was matched by an approximately 30% decrease in root-mean-square error and around 100% increase in Nash–Sutcliffe efficiency. Such a promising accuracy in the proposed model may recommend its application at monthly rainfall forecasting in the present semiarid region.en_US
dc.description.sponsorshipNo sponsoren_US
dc.publisherSpringer Berlin Heidelbergen_US
dc.subjectSupport vector regressionen_US
dc.subjectTime series modelingen_US
dc.subjectFirefly algorithmen_US
dc.subjectMultigene genetic programmingen_US
dc.subjectDestek vektör regresyontr_TR
dc.subjectYağış miktarıtr_TR
dc.subjectZaman serileri modellemesitr_TR
dc.subjectAteş böceği algoritmasıtr_TR
dc.subjectMultigen genetik programlamatr_TR
dc.titleA hybrid support vector regression-firefly model for monthly rainfall forecastingen_US
dc.relation.publicationcategoryInternational publicationen_US
dc.contributor.orcid0000-0003-2769-106X [Danandeh Mehr, Ali]
dc.contributor.abuauthorDanandeh Mehr, Ali
dc.contributor.yokid275430 [Danandeh Mehr, Ali]
dc.contributor.ScopusAuthorID55899085700 [Danandeh Mehr, Ali]

Files in this item


There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record