{"id":"https://openalex.org/W2899910325","doi":"https://doi.org/10.3390/data3040050","title":"Application of Rough Set Theory to Water Quality Analysis: A Case Study","display_name":"Application of Rough Set Theory to Water Quality Analysis: A Case Study","publication_year":2018,"publication_date":"2018-11-07","ids":{"openalex":"https://openalex.org/W2899910325","doi":"https://doi.org/10.3390/data3040050","mag":"2899910325"},"language":"en","primary_location":{"id":"doi:10.3390/data3040050","is_oa":true,"landing_page_url":"https://doi.org/10.3390/data3040050","pdf_url":"https://www.mdpi.com/2306-5729/3/4/50/pdf","source":{"id":"https://openalex.org/S4210226510","display_name":"Data","issn_l":"2306-5729","issn":["2306-5729"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2306-5729/3/4/50/pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5025056316","display_name":"Maryam Zavareh","orcid":"https://orcid.org/0000-0001-7318-6879"},"institutions":[{"id":"https://openalex.org/I162714631","display_name":"George Mason University","ror":"https://ror.org/02jqj7156","country_code":"US","type":"education","lineage":["https://openalex.org/I162714631"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Maryam Zavareh","raw_affiliation_strings":["Department of Civil, Environmental and Infrastructure Engineering, George Mason University, Fairfax, VA 22030, USA"],"raw_orcid":"https://orcid.org/0000-0001-7318-6879","affiliations":[{"raw_affiliation_string":"Department of Civil, Environmental and Infrastructure Engineering, George Mason University, Fairfax, VA 22030, USA","institution_ids":["https://openalex.org/I162714631"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083530998","display_name":"Viviana Maggioni","orcid":"https://orcid.org/0000-0003-0753-3179"},"institutions":[{"id":"https://openalex.org/I162714631","display_name":"George Mason University","ror":"https://ror.org/02jqj7156","country_code":"US","type":"education","lineage":["https://openalex.org/I162714631"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Viviana Maggioni","raw_affiliation_strings":["Department of Civil, Environmental and Infrastructure Engineering, George Mason University, Fairfax, VA 22030, USA"],"raw_orcid":"https://orcid.org/0000-0003-0753-3179","affiliations":[{"raw_affiliation_string":"Department of Civil, Environmental and Infrastructure Engineering, George Mason University, Fairfax, VA 22030, USA","institution_ids":["https://openalex.org/I162714631"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5025056316"],"corresponding_institution_ids":["https://openalex.org/I162714631"],"apc_list":{"value":1600,"currency":"CHF","value_usd":1732},"apc_paid":{"value":1600,"currency":"CHF","value_usd":1732},"fwci":1.2824,"has_fulltext":true,"cited_by_count":13,"citation_normalized_percentile":{"value":0.82931028,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"3","issue":"4","first_page":"50","last_page":"50"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T11490","display_name":"Hydrological Forecasting Using AI","score":0.9901000261306763,"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/T12543","display_name":"Groundwater and Watershed Analysis","score":0.9800999760627747,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/turbidity","display_name":"Turbidity","score":0.9072770476341248},{"id":"https://openalex.org/keywords/rough-set","display_name":"Rough set","score":0.6884217858314514},{"id":"https://openalex.org/keywords/water-quality","display_name":"Water quality","score":0.5960915088653564},{"id":"https://openalex.org/keywords/watershed","display_name":"Watershed","score":0.5883125066757202},{"id":"https://openalex.org/keywords/decision-rule","display_name":"Decision rule","score":0.4842219352722168},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4480382800102234},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.44764870405197144},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.37948259711265564},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.36208170652389526},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.35533326864242554},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.3482036888599396},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.13787636160850525},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.11826023459434509}],"concepts":[{"id":"https://openalex.org/C64016661","wikidata":"https://www.wikidata.org/wiki/Q898574","display_name":"Turbidity","level":2,"score":0.9072770476341248},{"id":"https://openalex.org/C111012933","wikidata":"https://www.wikidata.org/wiki/Q3137210","display_name":"Rough set","level":2,"score":0.6884217858314514},{"id":"https://openalex.org/C2780797713","wikidata":"https://www.wikidata.org/wiki/Q625376","display_name":"Water quality","level":2,"score":0.5960915088653564},{"id":"https://openalex.org/C150547873","wikidata":"https://www.wikidata.org/wiki/Q947851","display_name":"Watershed","level":2,"score":0.5883125066757202},{"id":"https://openalex.org/C84839998","wikidata":"https://www.wikidata.org/wiki/Q5249245","display_name":"Decision rule","level":2,"score":0.4842219352722168},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4480382800102234},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.44764870405197144},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.37948259711265564},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.36208170652389526},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.35533326864242554},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.3482036888599396},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.13787636160850525},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.11826023459434509},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3390/data3040050","is_oa":true,"landing_page_url":"https://doi.org/10.3390/data3040050","pdf_url":"https://www.mdpi.com/2306-5729/3/4/50/pdf","source":{"id":"https://openalex.org/S4210226510","display_name":"Data","issn_l":"2306-5729","issn":["2306-5729"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data","raw_type":"journal-article"},{"id":"pmh:oai:RePEc:gam:jdataj:v:3:y:2018:i:4:p:50-:d:181172","is_oa":false,"landing_page_url":"https://www.mdpi.com/2306-5729/3/4/50/","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},{"id":"pmh:oai:doaj.org/article:40baad9fa8d543ed808c6f636c8746c3","is_oa":true,"landing_page_url":"https://doaj.org/article/40baad9fa8d543ed808c6f636c8746c3","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Data, Vol 3, Iss 4, p 50 (2018)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2306-5729/3/4/50/","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3390/data3040050","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Data","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/data3040050","is_oa":true,"landing_page_url":"https://doi.org/10.3390/data3040050","pdf_url":"https://www.mdpi.com/2306-5729/3/4/50/pdf","source":{"id":"https://openalex.org/S4210226510","display_name":"Data","issn_l":"2306-5729","issn":["2306-5729"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.8199999928474426,"display_name":"Clean water and sanitation","id":"https://metadata.un.org/sdg/6"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2899910325.pdf","grobid_xml":"https://content.openalex.org/works/W2899910325.grobid-xml"},"referenced_works_count":25,"referenced_works":["https://openalex.org/W846647830","https://openalex.org/W1605948227","https://openalex.org/W1972973316","https://openalex.org/W1974882614","https://openalex.org/W1976727345","https://openalex.org/W2009567549","https://openalex.org/W2022625131","https://openalex.org/W2027511124","https://openalex.org/W2029336736","https://openalex.org/W2034672247","https://openalex.org/W2038819936","https://openalex.org/W2046473217","https://openalex.org/W2068673381","https://openalex.org/W2069324495","https://openalex.org/W2079972773","https://openalex.org/W2088166615","https://openalex.org/W2091285843","https://openalex.org/W2114357073","https://openalex.org/W2240907403","https://openalex.org/W2340020088","https://openalex.org/W2481009298","https://openalex.org/W2766098680","https://openalex.org/W2895184542","https://openalex.org/W4255833381","https://openalex.org/W6623530214"],"related_works":["https://openalex.org/W2607474063","https://openalex.org/W3018395630","https://openalex.org/W4239095282","https://openalex.org/W2362625891","https://openalex.org/W2387621747","https://openalex.org/W4214891796","https://openalex.org/W1021271351","https://openalex.org/W2389890090","https://openalex.org/W2370118692","https://openalex.org/W2519291612"],"abstract_inverted_index":{"This":[0],"work":[1],"proposes":[2],"an":[3],"approach":[4],"to":[5,61,68,80,89],"analyze":[6],"water":[7,19,137],"quality":[8,20,138],"data":[9,67],"that":[10,40,134],"is":[11,59,105,116,130,156,167,178,184,191,200],"based":[12,74],"on":[13,75],"rough":[14],"set":[15,57],"theory.":[16],"Six":[17],"major":[18],"indicators":[21,78,83,139],"(temperature,":[22],"pH,":[23],"dissolved":[24],"oxygen,":[25],"turbidity,":[26,179],"specific":[27,151,185,189],"conductivity,":[28],"and":[29,79,107,110,125,150,187],"nitrate":[30],"concentration)":[31],"were":[32],"collected":[33,66],"at":[34],"the":[35,38,42,65,76,91,99,108,126,135,141,145,162,170,175,180,192,195],"outlet":[36],"of":[37,64,102,112,165,172],"watershed":[39,143],"contains":[41],"George":[43],"Mason":[44,142],"University":[45],"campus":[46],"in":[47],"Fairfax,":[48],"VA":[49],"during":[50,144],"three":[51],"years":[52],"(October":[53],"2015\u2013December":[54],"2017).":[55],"Rough":[56],"theory":[58],"applied":[60],"monthly":[62],"averages":[63],"estimate":[69],"one":[70,171],"indicator":[71],"(decision":[72],"attribute)":[73],"remainder":[77],"determine":[81],"what":[82],"(conditional":[84],"attributes)":[85],"are":[86,97,122,148],"essential":[87],"(core)":[88],"predict":[90],"missing":[92],"indicator.":[93],"The":[94],"redundant":[95],"attributes":[96],"identified,":[98],"importance":[100,163],"degree":[101,164],"each":[103],"attribute":[104,177,183,197],"quantified,":[106],"certainty":[109,127],"coverage":[111,128],"any":[113],"detected":[114],"rule(s)":[115],"evaluated.":[117],"Possible":[118],"decision":[119,160,176,193],"making":[120],"rules":[121],"also":[123],"assessed":[124],"factor":[129],"calculated.":[131],"Results":[132],"show":[133],"core":[136],"for":[140],"study":[146],"period":[147],"turbidity":[149,166,199],"conductivity.":[152,173],"Particularly,":[153],"if":[154,188],"pH":[155],"chosen":[157],"as":[158],"a":[159],"attribute,":[161,194],"higher":[168],"than":[169],"If":[174],"only":[181],"indispensable":[182,196],"conductivity":[186,190],"beside":[198],"temperature.":[201]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}