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https://hdl.handle.net/11499/4327
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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Karahan, Halil | - |
dc.contributor.author | Ceylan, Halim. | - |
dc.contributor.author | Tamer Ayvaz, Mustafa | - |
dc.date.accessioned | 2019-08-16T11:33:26Z | - |
dc.date.available | 2019-08-16T11:33:26Z | - |
dc.date.issued | 2007 | - |
dc.identifier.issn | 0885-6087 | - |
dc.identifier.uri | https://hdl.handle.net/11499/4327 | - |
dc.identifier.uri | https://doi.org/10.1002/hyp.6245 | - |
dc.description.abstract | A genetic algorithm rainfall intensity (GARI) model has been developed and used to predict the intensities for given return period. It is a one-step solution procedure that may not require any mathematical transformation. The problem formulation is given and the genetic algorithm solution of the problem is presented. The results show that the proposed GARI model can be used to solve the rainfall intensity-duration-frequency relations with lowest mean-squared error between measured and predicted intensities. Predicted intensities are in good agreement between measured and predicted values for given return period. Copyright © 2006 John Wiley & Sons, Ltd. | en_US |
dc.language.iso | en | en_US |
dc.relation.ispartof | Hydrological Processes | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | Genetic algorithm | en_US |
dc.subject | Parameter estimation | en_US |
dc.subject | Rainfall intensity | en_US |
dc.subject | Genetic algorithms | en_US |
dc.subject | Mathematical models | en_US |
dc.subject | Mathematical transformations | en_US |
dc.subject | Mean square error | en_US |
dc.subject | Rain | en_US |
dc.subject | Genetic algorithm rainfall intensity (GARI) model | en_US |
dc.subject | Rainfall intensity-duration-frequency relations | en_US |
dc.subject | Weather forecasting | en_US |
dc.subject | estimation method | en_US |
dc.subject | genetic algorithm | en_US |
dc.subject | parameterization | en_US |
dc.subject | precipitation assessment | en_US |
dc.subject | precipitation intensity | en_US |
dc.subject | prediction | en_US |
dc.subject | return period | en_US |
dc.title | Predicting rainfall intensity using a genetic algorithm approach | en_US |
dc.type | Article | en_US |
dc.identifier.volume | 21 | en_US |
dc.identifier.issue | 4 | en_US |
dc.identifier.startpage | 470 | - |
dc.identifier.startpage | 470 | en_US |
dc.identifier.endpage | 475 | en_US |
dc.authorid | 0000-0001-5346-5686 | - |
dc.authorid | 0000-0002-4616-5439 | - |
dc.authorid | 0000-0002-8566-2825 | - |
dc.identifier.doi | 10.1002/hyp.6245 | - |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
dc.identifier.scopus | 2-s2.0-33847019533 | en_US |
dc.identifier.wos | WOS:000244308200005 | en_US |
local.message.claim | 2024-08-23T13:49:55.847+0300|||null|||submit_approve|||dc_contributor_author|||None | * |
dc.identifier.scopusquality | Q1 | - |
dc.owner | Pamukkale_University | - |
item.fulltext | No Fulltext | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.cerifentitytype | Publications | - |
item.languageiso639-1 | en | - |
item.grantfulltext | none | - |
item.openairetype | Article | - |
crisitem.author.dept | 10.02. Civil Engineering | - |
crisitem.author.dept | 10.02. Civil Engineering | - |
crisitem.author.dept | 10.02. Civil Engineering | - |
Appears in Collections: | Mühendislik Fakültesi Koleksiyonu Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection |
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