{"id":"https://openalex.org/W2229973520","doi":"https://doi.org/10.1080/0952813x.2015.1042531","title":"Prediction of dissolved oxygen in River Calder by noise elimination time series using wavelet transform","display_name":"Prediction of dissolved oxygen in River Calder by noise elimination time series using wavelet transform","publication_year":2015,"publication_date":"2015-05-26","ids":{"openalex":"https://openalex.org/W2229973520","doi":"https://doi.org/10.1080/0952813x.2015.1042531","mag":"2229973520"},"language":"en","primary_location":{"id":"doi:10.1080/0952813x.2015.1042531","is_oa":false,"landing_page_url":"https://doi.org/10.1080/0952813x.2015.1042531","pdf_url":null,"source":{"id":"https://openalex.org/S153467142","display_name":"Journal of Experimental & Theoretical Artificial Intelligence","issn_l":"0952-813X","issn":["0952-813X","1362-3079"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Experimental & Theoretical Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://hdl.handle.net/11129/2450","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5009213794","display_name":"Masoud Ravansalar","orcid":"https://orcid.org/0000-0002-6708-7484"},"institutions":[{"id":"https://openalex.org/I36515993","display_name":"Eastern Mediterranean University","ror":"https://ror.org/00excyz84","country_code":"CY","type":"education","lineage":["https://openalex.org/I36515993"]}],"countries":["CY"],"is_corresponding":true,"raw_author_name":"Masoud Ravansalar","raw_affiliation_strings":["Department of Civil Engineering, Eastern Mediterranean University, Famagusta, Northern Cyprus, Via Mersin-10, Turkey"],"affiliations":[{"raw_affiliation_string":"Department of Civil Engineering, Eastern Mediterranean University, Famagusta, Northern Cyprus, Via Mersin-10, Turkey","institution_ids":["https://openalex.org/I36515993"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080922026","display_name":"Taher Rajaee","orcid":"https://orcid.org/0000-0002-4325-2537"},"institutions":[{"id":"https://openalex.org/I184468904","display_name":"University of Qom","ror":"https://ror.org/03ddeer04","country_code":"IR","type":"education","lineage":["https://openalex.org/I184468904"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Taher Rajaee","raw_affiliation_strings":["Department of Civil Engineering, University of Qom, Qom, Iran"],"affiliations":[{"raw_affiliation_string":"Department of Civil Engineering, University of Qom, Qom, Iran","institution_ids":["https://openalex.org/I184468904"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089264392","display_name":"Mustafa Ergil","orcid":null},"institutions":[{"id":"https://openalex.org/I36515993","display_name":"Eastern Mediterranean University","ror":"https://ror.org/00excyz84","country_code":"CY","type":"education","lineage":["https://openalex.org/I36515993"]}],"countries":["CY"],"is_corresponding":false,"raw_author_name":"Mustafa Ergil","raw_affiliation_strings":["Department of Civil Engineering, Eastern Mediterranean University, Famagusta, Northern Cyprus, Via Mersin-10, Turkey"],"affiliations":[{"raw_affiliation_string":"Department of Civil Engineering, Eastern Mediterranean University, Famagusta, Northern Cyprus, Via Mersin-10, Turkey","institution_ids":["https://openalex.org/I36515993"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5009213794"],"corresponding_institution_ids":["https://openalex.org/I36515993"],"apc_list":null,"apc_paid":null,"fwci":2.097,"has_fulltext":false,"cited_by_count":33,"citation_normalized_percentile":{"value":0.860938,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"28","issue":"4","first_page":"689","last_page":"706"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11490","display_name":"Hydrological Forecasting Using AI","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11490","display_name":"Hydrological Forecasting Using AI","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10330","display_name":"Hydrology and Watershed Management Studies","score":0.9952999949455261,"subfield":{"id":"https://openalex.org/subfields/2312","display_name":"Water Science and Technology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":0.9800999760627747,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/discrete-wavelet-transform","display_name":"Discrete wavelet transform","score":0.6082727909088135},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.579865574836731},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.5788995027542114},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5267452597618103},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.5185964107513428},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4932653307914734},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.48041343688964844},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.4767104983329773},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.36511969566345215},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3558850884437561},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.34077394008636475},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.16408944129943848}],"concepts":[{"id":"https://openalex.org/C46286280","wikidata":"https://www.wikidata.org/wiki/Q2414958","display_name":"Discrete wavelet transform","level":4,"score":0.6082727909088135},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.579865574836731},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.5788995027542114},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5267452597618103},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.5185964107513428},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4932653307914734},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.48041343688964844},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4767104983329773},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.36511969566345215},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3558850884437561},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34077394008636475},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.16408944129943848},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1080/0952813x.2015.1042531","is_oa":false,"landing_page_url":"https://doi.org/10.1080/0952813x.2015.1042531","pdf_url":null,"source":{"id":"https://openalex.org/S153467142","display_name":"Journal of Experimental & Theoretical Artificial Intelligence","issn_l":"0952-813X","issn":["0952-813X","1362-3079"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Experimental & Theoretical Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:i-rep.emu.edu.tr:11129/2450","is_oa":true,"landing_page_url":"http://hdl.handle.net/11129/2450","pdf_url":null,"source":{"id":"https://openalex.org/S4306402300","display_name":"Eastern Mediterranean University Institutional Repository (Eastern Mediterranean University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I36515993","host_organization_name":"Eastern Mediterranean University","host_organization_lineage":["https://openalex.org/I36515993"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:i-rep.emu.edu.tr:11129/2450","is_oa":true,"landing_page_url":"http://hdl.handle.net/11129/2450","pdf_url":null,"source":{"id":"https://openalex.org/S4306402300","display_name":"Eastern Mediterranean University Institutional Repository (Eastern Mediterranean University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I36515993","host_organization_name":"Eastern Mediterranean University","host_organization_lineage":["https://openalex.org/I36515993"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"article"},"sustainable_development_goals":[{"display_name":"Clean water and sanitation","score":0.8500000238418579,"id":"https://metadata.un.org/sdg/6"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W1518010084","https://openalex.org/W1533618852","https://openalex.org/W1554663460","https://openalex.org/W1592972299","https://openalex.org/W1965197372","https://openalex.org/W1975183682","https://openalex.org/W1976944686","https://openalex.org/W1984937336","https://openalex.org/W1991091044","https://openalex.org/W1993263428","https://openalex.org/W2002351729","https://openalex.org/W2003756933","https://openalex.org/W2017249431","https://openalex.org/W2018816284","https://openalex.org/W2024520223","https://openalex.org/W2029724692","https://openalex.org/W2031240721","https://openalex.org/W2033904036","https://openalex.org/W2035811055","https://openalex.org/W2041534329","https://openalex.org/W2042951562","https://openalex.org/W2042985051","https://openalex.org/W2043449394","https://openalex.org/W2051030695","https://openalex.org/W2052326365","https://openalex.org/W2063756720","https://openalex.org/W2065283082","https://openalex.org/W2070986256","https://openalex.org/W2083170793","https://openalex.org/W2094618865","https://openalex.org/W2095547201","https://openalex.org/W2101133595","https://openalex.org/W2115755118","https://openalex.org/W2140362372","https://openalex.org/W2155433156","https://openalex.org/W2155482699","https://openalex.org/W4210925605","https://openalex.org/W4299101042","https://openalex.org/W4388297464","https://openalex.org/W6631732916","https://openalex.org/W6677399427","https://openalex.org/W7081430716"],"related_works":["https://openalex.org/W183670115","https://openalex.org/W4245420407","https://openalex.org/W1501179639","https://openalex.org/W3199035354","https://openalex.org/W2085792030","https://openalex.org/W4401371153","https://openalex.org/W1807354010","https://openalex.org/W3143644526","https://openalex.org/W598225674","https://openalex.org/W1588899229"],"abstract_inverted_index":{"Prediction":[0],"of":[1,25,92,131,158,186,189,202,219],"dissolved":[2,49],"oxygen":[3,20,50],"(DO)":[4],"plays":[5],"an":[6],"important":[7],"role":[8],"in":[9,13,51,62,101,165,172,224],"water":[10,27],"resources":[11],"especially":[12],"surface":[14],"waters":[15],"such":[16],"as":[17],"rivers.":[18],"The":[19,117,125,139,154],"affects":[21],"a":[22,38],"vast":[23],"number":[24],"other":[26],"indicators.":[28],"In":[29],"this":[30,86,211],"study,":[31],"the":[32,52,56,63,66,70,78,88,114,132,148,161,173,187,190,197,203,208,217],"artificial":[33],"neural":[34],"network":[35],"(ANN)":[36],"and":[37,96,107,145,150],"hybrid":[39],"wavelet-ANN":[40],"(WANN)":[41],"models":[42],"were":[43,99,111,119,127,143,164],"considered":[44],"to":[45,77,113,193],"predict":[46],"thirty":[47,93,225],"minutes":[48,94,226],"River":[53],"Calder":[54],"at":[55],"Methley":[57],"Bridge":[58],"Station":[59],"was":[60,75],"located":[61],"UK.":[64],"For":[65],"proposed":[67],"WANN":[68,149,162,191,209],"model,":[69,210],"discrete":[71],"wavelet":[72],"transform":[73],"(DWT)":[74],"linked":[76],"ANN":[79,115,123,151],"model":[80,155,163,180,192,212],"for":[81,147,216],"DO":[82,95,159,205,221],"prediction.":[83,195],"To":[84],"achieve":[85],"aim,":[87],"original":[89],"time":[90],"series":[91,104],"temperature":[97],"(T)":[98],"decomposed":[100],"several":[102],"sub-time":[103],"by":[105,129,160,178,207],"DWT,":[106],"these":[108],"new":[109],"sub-series":[110],"imposed":[112],"model.":[116,124],"results":[118,198],"compared":[120],"with":[121,168],"single":[122],"comparisons":[126],"done":[128],"some":[130],"widely":[133],"used":[134,215],"relevant":[135],"physical":[136],"statistic":[137],"indices.":[138],"Nash\u2013Sutcliffe":[140],"coefficient":[141],"values":[142,157,171,206],"0.998":[144],"0.740":[146],"models,":[152],"respectively.":[153],"computed":[156],"close":[166],"agreement":[167],"respective":[169],"measured":[170],"river":[174],"water.":[175],"Elimination":[176],"noise":[177],"DWT":[179],"during":[181],"pre-processing":[182],"data":[183,222],"is":[184],"one":[185],"abilities":[188],"better":[194],"Since":[196],"indicate":[199],"closer":[200],"approximation":[201],"peak":[204],"could":[213],"be":[214],"simulation":[218],"cumulative":[220],"prediction":[223],"ahead.":[227]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":2}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}