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For this real time project work, Yen Bai station, Northwest Vietnam was chosen as an experimental case study to apply the proposed model. Input variables into the Wavelet-ANN structure is water level data. Time series and ANN models are built, and their performances are compared. The results indicate the greater accuracy of the proposed models at Hanoi station. The final proposal WAANN\u2212TS for water level forecasting shows good performance with root mean square error (RMSE) from 10\u221210 to 10\u221211.<\/p>","DOI":"10.4018\/ijirr.2020070101","type":"journal-article","created":{"date-parts":[[2020,6,17]],"date-time":"2020-06-17T10:05:09Z","timestamp":1592388309000},"page":"1-19","source":"Crossref","is-referenced-by-count":3,"title":["Prediction of Water Level Using Time Series, Wavelet and Neural Network Approaches"],"prefix":"10.4018","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5988-3651","authenticated-orcid":true,"given":"Nguyen Quang","family":"Dat","sequence":"first","affiliation":[{"name":"Hanoi University of Science and Technology, Hanoi, Vietnam"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6555-9740","authenticated-orcid":true,"given":"Ngoc Anh Nguyen","family":"Thi","sequence":"additional","affiliation":[{"name":"Hanoi University of Science and Technology, Hanoi, Vietnam"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5784-1052","authenticated-orcid":true,"given":"Vijender Kumar","family":"Solanki","sequence":"additional","affiliation":[{"name":"CMR institute of Technology (Autonomous), Hyderabad, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6527-4745","authenticated-orcid":true,"given":"Ngo","family":"Le An","sequence":"additional","affiliation":[{"name":"Thuyloi University, Hanoi, Vietnam"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"2432","reference":[{"key":"IJIRR.2020070101-0","doi-asserted-by":"publisher","DOI":"10.1016\/j.jhydrol.2011.06.013"},{"key":"IJIRR.2020070101-1","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2014.05.028"},{"key":"IJIRR.2020070101-2","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2009.10.013"},{"key":"IJIRR.2020070101-3","doi-asserted-by":"publisher","DOI":"10.1016\/j.jhydrol.2013.10.052"},{"issue":"1","key":"IJIRR.2020070101-4","first-page":"3","article-title":"A seasonal - trend decomposition procedure based on Loess.","volume":"6","author":"R. 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