{"id":"https://openalex.org/W2015197546","doi":"https://doi.org/10.9720/kseg.2013.2.137","title":"Application of groundwater-level prediction models using data-based learning algorithms to National Groundwater Monitoring Network data","display_name":"Application of groundwater-level prediction models using data-based learning algorithms to National Groundwater Monitoring Network data","publication_year":2013,"publication_date":"2013-06-30","ids":{"openalex":"https://openalex.org/W2015197546","doi":"https://doi.org/10.9720/kseg.2013.2.137","mag":"2015197546"},"language":"en","primary_location":{"id":"doi:10.9720/kseg.2013.2.137","doi":"https://doi.org/10.9720/kseg.2013.2.137","is_oa":true,"landing_page_url":"https://doi.org/10.9720/kseg.2013.2.137","pdf_url":"http://koreascience.or.kr:80/article/JAKO201322836623098.pdf","source":{"id":"https://openalex.org/S4306532325","display_name":"The Journal of Engineering Geology","issn_l":"1226-5268","issn":["1226-5268","2287-7169"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["kci-registered","poland-20","russia-white-list-4"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The Journal of Engineering Geology","raw_type":"journal-article"},"parent_works":[],"lineage":["https://openalex.org/W2015197546"],"child_works_count":0,"type":"article","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"http://koreascience.or.kr:80/article/JAKO201322836623098.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103079557","display_name":"Heesung Yoon","orcid":"https://orcid.org/0000-0001-7214-9291","observed_orcids":["https://orcid.org/0000-0001-7214-9291"]},"institutions":[{"id":"https://openalex.org/I4210142421","display_name":"Korea Institute of Geoscience and Mineral Resources","ror":"https://ror.org/044k0pw44","country_code":"KR","type":"facility","lineage":["https://openalex.org/I4210142421"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Heesung Yoon","raw_affiliation_strings":["Korea Institute of Geoscience and Mineral Resources"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Korea Institute of Geoscience and Mineral Resources","institution_ids":["https://openalex.org/I4210142421"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102002615","display_name":"Yongcheol Kim","orcid":"https://orcid.org/0000-0002-2475-5147","observed_orcids":["https://orcid.org/0000-0002-2475-5147"]},"institutions":[{"id":"https://openalex.org/I4210142421","display_name":"Korea Institute of Geoscience and Mineral Resources","ror":"https://ror.org/044k0pw44","country_code":"KR","type":"facility","lineage":["https://openalex.org/I4210142421"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Yongcheol Kim","raw_affiliation_strings":["Korea Institute of Geoscience and Mineral Resources"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Korea Institute of Geoscience and Mineral Resources","institution_ids":["https://openalex.org/I4210142421"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084176970","display_name":"Kyoochul Ha","orcid":"https://orcid.org/0000-0002-2682-5479","observed_orcids":["https://orcid.org/0000-0002-2682-5479"]},"institutions":[{"id":"https://openalex.org/I4210142421","display_name":"Korea Institute of Geoscience and Mineral Resources","ror":"https://ror.org/044k0pw44","country_code":"KR","type":"facility","lineage":["https://openalex.org/I4210142421"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Kyoochul Ha","raw_affiliation_strings":["Korea Institute of Geoscience and Mineral Resources"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Korea Institute of Geoscience and Mineral Resources","institution_ids":["https://openalex.org/I4210142421"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030818308","display_name":"Gyoo-Bum Kim","orcid":"https://orcid.org/0000-0001-6556-2045","observed_orcids":["https://orcid.org/0000-0001-6556-2045"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gyoo-Bum Kim","raw_affiliation_strings":["Geowater+ Research Center , K-water Institute"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Geowater+ Research Center , K-water Institute","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.4994,"has_fulltext":true,"cited_by_count":8,"citation_normalized_percentile":{"value":0.80233417,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":97},"biblio":{"volume":"23","issue":"2","first_page":"137","last_page":"147"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11490","display_name":"Hydrological Forecasting Using AI","score":1.0,"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":1.0,"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/T10320","display_name":"Neural Networks and Applications","score":0.0,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10398","display_name":"Groundwater and Isotope Geochemistry","score":0.0,"subfield":{"id":"https://openalex.org/subfields/1906","display_name":"Geochemistry and Petrology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/groundwater-level-forecasting","display_name":"groundwater level prediction","score":0.9240000247955322},{"id":"https://openalex.org/keywords/neural-network","display_name":"artificial neural networks","score":0.843999981880188},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"support vector machine","score":1.0},{"id":"https://openalex.org/keywords/time-series-forecasting","display_name":"time series forecasting","score":0.8130000233650208},{"id":"https://openalex.org/keywords/feature-selection","display_name":"feature selection","score":0.6169999837875366},{"id":"https://openalex.org/keywords/groundwater-management","display_name":"groundwater management","score":0.6449999809265137},{"id":"https://openalex.org/keywords/prediction-error-correction","display_name":"prediction error correction","score":0.4090000092983246}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.8137280941009521},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6754245162010193},{"id":"https://openalex.org/C76177295","wikidata":"https://www.wikidata.org/wiki/Q161598","display_name":"Groundwater","level":2,"score":0.6508446931838989},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.5406038761138916},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5273129343986511},{"id":"https://openalex.org/C2780092901","wikidata":"https://www.wikidata.org/wiki/Q3433612","display_name":"Correlation coefficient","level":2,"score":0.5081591606140137},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5032309889793396},{"id":"https://openalex.org/C146357865","wikidata":"https://www.wikidata.org/wiki/Q1123245","display_name":"Stage (stratigraphy)","level":2,"score":0.4595244526863098},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.44885727763175964},{"id":"https://openalex.org/C2993807900","wikidata":"https://www.wikidata.org/wiki/Q1049799","display_name":"Groundwater resources","level":4,"score":0.4475657045841217},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41890352964401245},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.38816404342651367},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1642768383026123},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.11732330918312073},{"id":"https://openalex.org/C187320778","wikidata":"https://www.wikidata.org/wiki/Q1349130","display_name":"Geotechnical engineering","level":1,"score":0.10724839568138123},{"id":"https://openalex.org/C75622301","wikidata":"https://www.wikidata.org/wiki/Q208791","display_name":"Aquifer","level":3,"score":0.10530036687850952},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.9720/kseg.2013.2.137","doi":"https://doi.org/10.9720/kseg.2013.2.137","is_oa":true,"landing_page_url":"https://doi.org/10.9720/kseg.2013.2.137","pdf_url":"http://koreascience.or.kr:80/article/JAKO201322836623098.pdf","source":{"id":"https://openalex.org/S4306532325","display_name":"The Journal of Engineering Geology","issn_l":"1226-5268","issn":["1226-5268","2287-7169"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["kci-registered","poland-20","russia-white-list-4"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The Journal of Engineering Geology","raw_type":"journal-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.863.5398","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.863.5398","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://ocean.kisti.re.kr/downfile/volume/kseg/JJGHBG/2013/v23n2/JJGHBG_2013_v23n2_137.pdf","raw_type":"text"},{"id":"mag:2396165296","doi":null,"is_oa":false,"landing_page_url":"http://dspace.kci.go.kr/handle/kci/1068732?show=full","pdf_url":null,"source":{"id":"https://openalex.org/S4306532325","display_name":"The Journal of Engineering Geology","issn_l":"1226-5268","issn":["1226-5268","2287-7169"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["kci-registered","poland-20","russia-white-list-4"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"\uc9c0\uc9c8\uacf5\ud559 = The journal of engineering geology","raw_type":null}],"best_oa_location":{"id":"doi:10.9720/kseg.2013.2.137","doi":"https://doi.org/10.9720/kseg.2013.2.137","is_oa":true,"landing_page_url":"https://doi.org/10.9720/kseg.2013.2.137","pdf_url":"http://koreascience.or.kr:80/article/JAKO201322836623098.pdf","source":{"id":"https://openalex.org/S4306532325","display_name":"The Journal of Engineering Geology","issn_l":"1226-5268","issn":["1226-5268","2287-7169"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["kci-registered","poland-20","russia-white-list-4"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The Journal of Engineering Geology","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Clean water and sanitation","id":"https://metadata.un.org/sdg/6","score":0.965499997138977}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2015197546.pdf","grobid_xml":"https://content.openalex.org/works/W2015197546.grobid-xml"},"referenced_works_count":24,"referenced_works":["https://openalex.org/W740415","https://openalex.org/W1512098439","https://openalex.org/W1560724230","https://openalex.org/W1580822624","https://openalex.org/W1618006338","https://openalex.org/W1964340924","https://openalex.org/W1974250802","https://openalex.org/W1982773244","https://openalex.org/W1983520151","https://openalex.org/W2004041476","https://openalex.org/W2019451733","https://openalex.org/W2025651937","https://openalex.org/W2028003655","https://openalex.org/W2028802401","https://openalex.org/W2036535026","https://openalex.org/W2043078134","https://openalex.org/W2048641690","https://openalex.org/W2080690725","https://openalex.org/W2090596876","https://openalex.org/W2127801933","https://openalex.org/W2156909104","https://openalex.org/W2165313910","https://openalex.org/W2170241183","https://openalex.org/W2313953460"],"related_works":["https://openalex.org/W2510812442","https://openalex.org/W980350170","https://openalex.org/W2273522817","https://openalex.org/W1897247022","https://openalex.org/W2311533087","https://openalex.org/W2999711155","https://openalex.org/W3026012730","https://openalex.org/W1969399508","https://openalex.org/W2952966233"],"abstract_inverted_index":{"\uc9c0\ud558\uc218\uc790\uc6d0\uc758":[0],"\ud6a8\uc728\uc801\uc778":[1,161],"\uad00\ub9ac\ub97c":[2],"\uc704\ud574":[3,64,94],"\uac15\uc6b0\uc5d0":[4],"\ub300\ud55c":[5,141],"\uc9c0\ud558\uc218\uc704":[6,31,58,73,82,89],"\ubcc0\ud654\ub97c":[7,83],"\uc608\uce21\ud558\ub294":[8,84],"\uac83\uc740":[9],"\uc911\uc694\ud55c":[10],"\ubb38\uc81c\uc774\ub2e4.":[11],"\ubcf8":[12,155],"\uc5f0\uad6c\uc5d0\uc11c\ub294":[13],"\uc790\ub8cc\uae30\ubc18":[14],"\ud559\uc2b5":[15],"\uc54c\uace0\ub9ac\uc998\uc778":[16],"\uc778\uacf5\uc2e0\uacbd\ub9dd\uacfc":[17],"\uc9c0\uc9c0\ubca1\ud130\uae30\uacc4\ub97c":[18],"\uc774\uc6a9\ud558\uc5ec":[19],"\uc2dc\uacc4\uc5f4":[20],"\uc608\uce21":[21,50,97,117,132,142],"\ubaa8\ub378\uc744":[22],"\ub9cc\ub4e4\uace0":[23],"\uc774\ub97c":[24],"\uad6d\uac00\uc9c0\ud558\uc218\uad00\uce21\ub9dd":[25],"\uc911":[26],"\uac00\uc0b0,":[27],"\uc2e0\uad11,":[28],"\uccad\uc131":[29],"\uad00\uce21\uc18c":[30,46],"\ubcc0\ud654":[32,62],"\uc608\uce21\uc5d0":[33],"\uc801\uc6a9\ud558\uc600\ub2e4.":[34],"\ubaa8\ub378\uc758":[35],"\uc785\ub825":[36,55,67,74,79,90],"\uc131\ubd84":[37,68],"\uad6c\uc131":[38],"\ubc29\ubc95\uc5d0":[39],"\ub530\ub77c":[40],"\ub124":[41],"\uac00\uc9c0":[42],"\ubaa8\ud615\uc744":[43],"\uc124\uc815\ud558\uace0":[44],"\uac01":[45],"\ubc0f":[47,60,72,88],"\ubaa8\ub378":[48,134],"\ubcc4":[49],"\uacb0\uacfc\ub97c":[51],"\ube44\uad50":[52],"\ud3c9\uac00\ud558\uc600\ub2e4.":[53,163],"\uac15\uc6b0":[54,71,87],"\ubaa8\ud615\uc758":[56,91,98,133],"\uacbd\uc6b0":[57,99],"\uac10\uc1e0":[59],"\uae30\uc800":[61],"\uc608\uce21\uc744":[63],"\ud070":[65,108],"\uaddc\ubaa8\uc758":[66,78],"\uad6c\uc131\uc774":[69],"\ud544\uc694\ud558\uc9c0\ub9cc":[70],"\ubaa8\ud615\uc740":[75],"\ubcf4\ub2e4":[76,159],"\uc791\uc740":[77],"\uc131\ubd84\uc73c\ub85c":[80],"\ud6a8\uacfc\uc801\uc73c\ub85c":[81],"\uac83\uc73c\ub85c":[85,109,128],"\ub098\ud0c0\ub0ac\ub2e4.":[86],"\ud65c\uc6a9\uc131":[92],"\uc99d\ub300\ub97c":[93],"\uace0\uc548\ub41c":[95],"\ubc18\ubcf5":[96,131],"\uad00\uce21\uac12\uacfc":[100],"\uc608\uce21\uac12":[101],"\uc0ac\uc774\uc5d0":[102],"0.75~0.95\uc758":[103],"\uc0c1\uad00\uacc4\uc218\ub97c":[104],"\ubcf4\uc5ec":[105],"\uc801\uc6a9":[106],"\uac00\ub2a5\uc131\uc774":[107],"\ud310\ub2e8\ub41c\ub2e4.":[110],"\uc804\uccb4\uc801\uc73c\ub85c":[111],"\uac15\uc6b0-\uc9c0\ud558\uc218\uc704":[112],"\uad50\ucc28\uc0c1\uad00\uacc4\uc218\uac00":[113],"\ub0ae\uc740":[114],"\uc2e0\uad11":[115],"\uad00\uce21\uc18c\uc758":[116],"\uc624\ucc28\uac00":[118],"\ud06c\uac8c":[119],"\ub098\ud0c0\ub0ac\uace0":[120],"ANN":[121,317,365],"\ubaa8\ub378\uc5d0":[122],"\ube44\ud574":[123],"SVM\uc758":[124,149],"\uc608\uce21\ub825\uc774":[125],"\ub2e4\uc18c":[126],"\ub192\uc740":[127],"\uc870\uc0ac\ub418\uc5c8\ub2e4.":[129],"\ub610\ud55c":[130],"\ud30c\ub77c\ubbf8\ud130":[135],"\uc120\uc815":[136],"\uacfc\uc815\uc5d0\uc11c":[137],"\ubcf4\uc815":[138],"\ub2e8\uacc4":[139,143],"\uc624\ucc28\uc5d0":[140],"\uc624\ucc28\uc758":[144],"\ube44\uc758":[145],"\ubd84\ud3ec\ub97c":[146],"\uc870\uc0ac\ud55c":[147],"\uacb0\uacfc":[148],"\uacbd\uc6b0\uac00":[150],"\ub354":[151],"\uc791\uac8c":[152],"\ub098\ud0c0\ub098":[153],"SVM\uc774":[154],"\uc5f0\uad6c":[156],"\uc790\ub8cc\uc5d0":[157],"\ub300\ud574":[158],"\uc548\uc815\uc801\uc774\uace0":[160],"\ubaa8\ub378\uc784\uc744":[162],"For":[164],"the":[165,185,211,218,241,250,257,264,296,302,305,324,329,334,339,345,350,353,359,364,370,379],"effective":[166,262,377],"management":[167],"of":[168,217,227,252,282,308,316,323,328,336,352],"groundwater":[169,176,207,253],"resources,":[170],"it":[171],"is":[172,245,261,299,355],"necessary":[173],"to":[174,181,206,230,342],"predict":[175],"level":[177,208],"fluctuations":[178],"in":[179,338,344],"response":[180],"rainfall":[182,242],"events.":[183],"In":[184],"present":[186,380],"study,":[187],"time":[188],"series":[189],"models":[190,275,310,318,361,372],"using":[191,333],"artificial":[192],"neural":[193],"networks":[194],"(ANNs)":[195],"and":[196,204,214,233,376],"support":[197],"vector":[198],"machines":[199],"(SVMs)":[200],"have":[201],"been":[202],"developed":[203],"applied":[205],"data":[209],"from":[210],"Gasan,":[212],"Shingwang,":[213],"Cheongseong":[215],"stations":[216],"National":[219],"Groundwater":[220],"Monitoring":[221],"Network.":[222],"We":[223],"designed":[224],"four":[225],"types":[226],"model":[228,244,260,271,306,325],"according":[229],"input":[231,243,259],"structure":[232],"compared":[234],"their":[235],"performances.":[236],"The":[237,287],"results":[238],"show":[239],"that":[240,315,343,349,369],"not":[246],"effective,":[247,278],"especially":[248],"for":[249,263,292,319,358,363,378],"prediction":[251,266,274,288,331],"recession":[254],"behavior;":[255],"however,":[256],"rainfall-groundwater":[258],"entire":[265],"stage,":[267,347],"yielding":[268,279],"a":[269],"high":[270],"accuracy.":[272],"Recursive":[273],"were":[276,290],"also":[277],"correlation":[280],"coefficients":[281],"0.75-0.95":[283],"with":[284],"observed":[285],"values.":[286],"errors":[289,337],"highest":[291],"Shingwang":[293],"station,":[294],"where":[295],"cross-correlation":[297],"coefficient":[298],"lowest":[300],"among":[301],"stations.":[303],"Overall,":[304],"performance":[307],"SVM":[309,360,371],"was":[311],"slightly":[312],"higher":[313],"than":[314,362],"all":[320],"cases.":[321],"Assessment":[322],"parameter":[326],"uncertainty":[327],"recursive":[330],"models,":[332,366],"ratio":[335,354],"validation":[340],"stage":[341],"calibration":[346],"showed":[348],"range":[351],"much":[356],"narrower":[357],"which":[367],"implies":[368],"are":[373],"more":[374],"stable":[375],"case":[381],"studies.":[382]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":4},{"year":2014,"cited_by_count":1}],"updated_date":"2026-11-14T11:04:58.165337","created_date":"2016-06-24T00:00:00"}