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Since the SVR has unknown parameters, the observer\u2010teacher\u2010learner\u2010based Optimization (OTLBO) method is integrated with the SVR model to provide a novel hybrid predictive model. The SVR combined with the genetic algorithm (SVR\u2010GA) is used as an alternative model. To explore the performance and application of the proposed models, five input combinations of rainfall and discharge data of Cham Siah River catchment are provided. The predictive models are assessed using various numerical and visual indicators. The results indicate that the SVR\u2010OTLBO model offers a higher prediction performance than other models employed in the current study. Specifically, SVR\u2010OTLBO model offers highest Pearson correlation coefficient (<jats:italic>R<\/jats:italic>\u2009=\u20090.9768), Willmott\u2019s Index (WI\u2009=\u20090.9812), ratio of performance to IQ (RPIQ\u2009=\u20090.9201), and modified index of agreement (md\u2009=\u20090.7411) and the lowest relative root mean square error (RRMSE\u2009=\u20090.5371) in comparison with SVR\u2010GA (<jats:italic>R<\/jats:italic>\u2009=\u20090.9704, WI\u2009=\u20090.9794, RPIQ\u2009=\u20090.8521, and md\u2009=\u20090.7323, 0.5617) and SVR (<jats:italic>R<\/jats:italic>\u2009=\u20090.9501, WI\u2009=\u20090.9734, RPIQ\u2009=\u20090.3229, md\u2009=\u20090.4338, and RRMSE\u2009=\u20091.0829) models, respectively.<\/jats:p>","DOI":"10.1155\/2021\/5540284","type":"journal-article","created":{"date-parts":[[2021,3,2]],"date-time":"2021-03-02T19:20:08Z","timestamp":1614712808000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":33,"title":["Estimation of Daily Suspended Sediment Load Using a Novel Hybrid Support Vector Regression Model Incorporated with Observer\u2010Teacher\u2010Learner\u2010Based Optimization Method"],"prefix":"10.1155","volume":"2021","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5855-8803","authenticated-orcid":false,"given":"Siyamak","family":"Doroudi","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0448-2871","authenticated-orcid":false,"given":"Ahmad","family":"Sharafati","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8056-293X","authenticated-orcid":false,"given":"Seyed Hossein","family":"Mohajeri","sequence":"additional","affiliation":[]}],"member":"311","published-online":{"date-parts":[[2021,3,2]]},"reference":[{"key":"e_1_2_8_1_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.scitotenv.2017.09.293"},{"key":"e_1_2_8_2_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.catena.2009.05.011"},{"key":"e_1_2_8_3_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.catena.2017.12.027"},{"key":"e_1_2_8_4_2","doi-asserted-by":"publisher","DOI":"10.1111\/j.1365-3091.2007.00940.x"},{"key":"e_1_2_8_5_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijsrc.2018.09.001"},{"key":"e_1_2_8_6_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11356-017-0713-8"},{"key":"e_1_2_8_7_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jhydrol.2012.06.019"},{"key":"e_1_2_8_8_2","doi-asserted-by":"publisher","DOI":"10.1061\/(ASCE)0733-9429(2000)126:8(578)"},{"key":"e_1_2_8_9_2","doi-asserted-by":"publisher","DOI":"10.1061\/(ASCE)0733-9429(2008)134:8(1142)"},{"key":"e_1_2_8_10_2","article-title":"Sedimentation engineering: processes, measurements, modeling and practice","author":"Garcia M. 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