{"id":"https://openalex.org/W2050920748","doi":"https://doi.org/10.1080/08839510802226785","title":"ENSEMBLE ARTIFICIAL NEURAL NETWORKS FOR PREDICTION OF DEW POINT TEMPERATURE","display_name":"ENSEMBLE ARTIFICIAL NEURAL NETWORKS FOR PREDICTION OF DEW POINT TEMPERATURE","publication_year":2008,"publication_date":"2008-07-18","ids":{"openalex":"https://openalex.org/W2050920748","doi":"https://doi.org/10.1080/08839510802226785","mag":"2050920748"},"language":"en","primary_location":{"id":"doi:10.1080/08839510802226785","is_oa":true,"landing_page_url":"https://doi.org/10.1080/08839510802226785","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/08839510802226785?needAccess=true&role=button","source":{"id":"https://openalex.org/S125501549","display_name":"Applied Artificial Intelligence","issn_l":"0883-9514","issn":["0883-9514","1087-6545"],"is_oa":false,"is_in_doaj":true,"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":"Applied Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://www.tandfonline.com/doi/pdf/10.1080/08839510802226785?needAccess=true&role=button","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5079314626","display_name":"Daniel B. Shank","orcid":"https://orcid.org/0000-0002-3746-2407"},"institutions":[{"id":"https://openalex.org/I165733156","display_name":"University of Georgia","ror":"https://ror.org/00te3t702","country_code":"US","type":"education","lineage":["https://openalex.org/I165733156"]},{"id":"https://openalex.org/I4210164862","display_name":"Artificial Intelligence in Medicine (Canada)","ror":"https://ror.org/05p590m36","country_code":"CA","type":"company","lineage":["https://openalex.org/I4210164862"]}],"countries":["CA","US"],"is_corresponding":false,"raw_author_name":"D. B. Shank","raw_affiliation_strings":["Artificial Intelligence Center, University of Georgia","Artificial Intelligence Center, University of Georgia, Athens, Georgia, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Artificial Intelligence Center, University of Georgia","institution_ids":["https://openalex.org/I4210164862"]},{"raw_affiliation_string":"Artificial Intelligence Center, University of Georgia, Athens, Georgia, USA","institution_ids":["https://openalex.org/I165733156"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000373577","display_name":"R. W. McClendon","orcid":null},"institutions":[{"id":"https://openalex.org/I165733156","display_name":"University of Georgia","ror":"https://ror.org/00te3t702","country_code":"US","type":"education","lineage":["https://openalex.org/I165733156"]},{"id":"https://openalex.org/I4210164862","display_name":"Artificial Intelligence in Medicine (Canada)","ror":"https://ror.org/05p590m36","country_code":"CA","type":"company","lineage":["https://openalex.org/I4210164862"]}],"countries":["CA","US"],"is_corresponding":false,"raw_author_name":"R. W. McClendon","raw_affiliation_strings":["Artificial Intelligence Center, University of Georgia","Driftmier Engineering Center, University of Georgia","Artificial Intelligence Center, University of Georgia, Athens, Georgia, USA,Department of Biological and Agricultural Engineering, Driftmier Engineering Center, University of Georgia, Athens, Geor ...#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Artificial Intelligence Center, University of Georgia","institution_ids":["https://openalex.org/I4210164862"]},{"raw_affiliation_string":"Driftmier Engineering Center, University of Georgia","institution_ids":["https://openalex.org/I165733156"]},{"raw_affiliation_string":"Artificial Intelligence Center, University of Georgia, Athens, Georgia, USA,Department of Biological and Agricultural Engineering, Driftmier Engineering Center, University of Georgia, Athens, Geor ...#TAB#","institution_ids":["https://openalex.org/I165733156"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045841901","display_name":"Joel O. Paz","orcid":"https://orcid.org/0000-0003-0193-3681"},"institutions":[{"id":"https://openalex.org/I165733156","display_name":"University of Georgia","ror":"https://ror.org/00te3t702","country_code":"US","type":"education","lineage":["https://openalex.org/I165733156"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"J. Paz","raw_affiliation_strings":["University of Georgia","Department of Biological and Agricultural Engineering, University of Georgia, Griffin, Georgia, USA#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Georgia","institution_ids":[]},{"raw_affiliation_string":"Department of Biological and Agricultural Engineering, University of Georgia, Griffin, Georgia, USA#TAB#","institution_ids":["https://openalex.org/I165733156"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047677277","display_name":"Gerrit Hoogenboom","orcid":"https://orcid.org/0000-0002-1555-0537"},"institutions":[{"id":"https://openalex.org/I165733156","display_name":"University of Georgia","ror":"https://ror.org/00te3t702","country_code":"US","type":"education","lineage":["https://openalex.org/I165733156"]},{"id":"https://openalex.org/I4210164862","display_name":"Artificial Intelligence in Medicine (Canada)","ror":"https://ror.org/05p590m36","country_code":"CA","type":"company","lineage":["https://openalex.org/I4210164862"]}],"countries":["CA","US"],"is_corresponding":true,"raw_author_name":"G. Hoogenboom","raw_affiliation_strings":["Artificial Intelligence Center, University of Georgia","University of Georgia","Artificial Intelligence Center, University of Georgia , Athens, Georgia, USA ; Department of Biological and Agricultural Engineering , University of Georgia , Griffin, Georgia, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Artificial Intelligence Center, University of Georgia","institution_ids":["https://openalex.org/I4210164862"]},{"raw_affiliation_string":"University of Georgia","institution_ids":[]},{"raw_affiliation_string":"Artificial Intelligence Center, University of Georgia , Athens, Georgia, USA ; Department of Biological and Agricultural Engineering , University of Georgia , Griffin, Georgia, USA","institution_ids":["https://openalex.org/I165733156"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5047677277"],"corresponding_institution_ids":["https://openalex.org/I165733156","https://openalex.org/I4210164862"],"apc_list":{"value":2195,"currency":"USD","value_usd":2195},"apc_paid":null,"fwci":1.6669,"has_fulltext":true,"cited_by_count":34,"citation_normalized_percentile":{"value":0.83024492,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"22","issue":"6","first_page":"523","last_page":"542"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12120","display_name":"Air Quality Monitoring and Forecasting","score":0.9965000152587891,"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/T12120","display_name":"Air Quality Monitoring and Forecasting","score":0.9965000152587891,"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/T11490","display_name":"Hydrological Forecasting Using AI","score":0.9951000213623047,"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/T11276","display_name":"Solar Radiation and Photovoltaics","score":0.9869999885559082,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/dew-point","display_name":"Dew point","score":0.9101169109344482},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6883499622344971},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.667227029800415},{"id":"https://openalex.org/keywords/dew","display_name":"Dew","score":0.6409273743629456},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4234643280506134},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.380914568901062},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.29966849088668823},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.28535234928131104},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21886205673217773}],"concepts":[{"id":"https://openalex.org/C82210777","wikidata":"https://www.wikidata.org/wiki/Q178828","display_name":"Dew point","level":2,"score":0.9101169109344482},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6883499622344971},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.667227029800415},{"id":"https://openalex.org/C64900583","wikidata":"https://www.wikidata.org/wiki/Q41097","display_name":"Dew","level":3,"score":0.6409273743629456},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4234643280506134},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.380914568901062},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.29966849088668823},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.28535234928131104},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21886205673217773},{"id":"https://openalex.org/C200093464","wikidata":"https://www.wikidata.org/wiki/Q166583","display_name":"Condensation","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/08839510802226785","is_oa":true,"landing_page_url":"https://doi.org/10.1080/08839510802226785","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/08839510802226785?needAccess=true&role=button","source":{"id":"https://openalex.org/S125501549","display_name":"Applied Artificial Intelligence","issn_l":"0883-9514","issn":["0883-9514","1087-6545"],"is_oa":false,"is_in_doaj":true,"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":"Applied Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1080/08839510802226785","is_oa":true,"landing_page_url":"https://doi.org/10.1080/08839510802226785","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/08839510802226785?needAccess=true&role=button","source":{"id":"https://openalex.org/S125501549","display_name":"Applied Artificial Intelligence","issn_l":"0883-9514","issn":["0883-9514","1087-6545"],"is_oa":false,"is_in_doaj":true,"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":"Applied Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306114","display_name":"U.S. Department of Agriculture","ror":"https://ror.org/01na82s61"},{"id":"https://openalex.org/F4320332787","display_name":"Risk Management Agency","ror":"https://ror.org/05222ev03"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2050920748.pdf","grobid_xml":"https://content.openalex.org/works/W2050920748.grobid-xml"},"referenced_works_count":35,"referenced_works":["https://openalex.org/W1493695866","https://openalex.org/W1493914388","https://openalex.org/W1498954346","https://openalex.org/W1516562244","https://openalex.org/W1578010480","https://openalex.org/W1838310486","https://openalex.org/W1937904385","https://openalex.org/W1964298122","https://openalex.org/W1977177161","https://openalex.org/W1978102254","https://openalex.org/W1986904371","https://openalex.org/W1997362017","https://openalex.org/W2003419268","https://openalex.org/W2011142156","https://openalex.org/W2017403098","https://openalex.org/W2022747340","https://openalex.org/W2026805690","https://openalex.org/W2038705170","https://openalex.org/W2041648773","https://openalex.org/W2060929823","https://openalex.org/W2075419637","https://openalex.org/W2088265251","https://openalex.org/W2101262589","https://openalex.org/W2114563684","https://openalex.org/W2124776405","https://openalex.org/W2150160348","https://openalex.org/W2159050930","https://openalex.org/W2170095398","https://openalex.org/W2482025096","https://openalex.org/W2612524549","https://openalex.org/W3016001898","https://openalex.org/W4249173910","https://openalex.org/W4253360490","https://openalex.org/W4255680123","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W2926365852","https://openalex.org/W2275929903","https://openalex.org/W4319591823","https://openalex.org/W1963670389","https://openalex.org/W2991787135","https://openalex.org/W2008769983","https://openalex.org/W2323427992","https://openalex.org/W2353023917","https://openalex.org/W1987576178","https://openalex.org/W2004159692"],"abstract_inverted_index":{"Dew":[0],"point":[1,38,211,227],"temperature":[2,39,228],"is":[3],"needed":[4],"as":[5],"an":[6,71,89,107,153],"input":[7],"to":[8,17,29,41,56,63,95,98,134,180,222],"calculate":[9],"various":[10],"meteorological":[11],"variables.":[12],"In":[13],"general,":[14],"it":[15],"contributes":[16],"human":[18],"and":[19,59,168,189],"animal":[20],"comfort":[21],"levels.":[22],"The":[23,142,174,213],"goal":[24],"of":[25,67,91,113,127,147],"this":[26,201],"study":[27],"was":[28,81],"develop":[30],"artificial":[31],"neural":[32],"network":[33],"(ANN)":[34],"models":[35,55,103,131,150,215],"for":[36,159,164,170,216,231],"dew":[37,210,226],"prediction":[40,218,229],"improve":[42],"upon":[43],"previous":[44,182],"research.":[45],"These":[46,129],"improvements":[47],"included":[48,157],"optimizing":[49],"the":[50,65,79,111,114,125,148,181,197,234],"stopping":[51,86],"criteria,":[52],"comparing":[53],"seasonal":[54,68],"year-round":[57,209],"models,":[58],"developing":[60],"ensemble":[61,108,130],"ANNs":[62],"blend":[64],"output":[66],"models.":[69,141],"For":[70],"ANN":[72,102,109,214],"trained":[73],"with":[74,110,152],"100,000":[75],"patterns":[76],"per":[77],"epoch,":[78],"error":[80],"reduced":[82,185],"using":[83,118],"a":[84,119,160,165,171,224],"2000-pattern":[85],"dataset":[87,156],"at":[88],"interval":[90],"20":[92],"learning":[93],"events":[94],"decide":[96],"when":[97,178],"stop":[99],"training.":[100],"Seasonal":[101],"were":[104,132,184,203,220],"blended":[105],"in":[106,200,205],"weight":[112],"member":[115],"networks":[116],"determined":[117],"fuzzy":[120],"membership-type":[121],"function":[122],"based":[123],"on":[124,233],"day":[126],"year.":[128],"shown":[133],"produce":[135],"lower":[136],"errors":[137,145],"than":[138],"year-round,":[139],"nonensemble":[140],"mean":[143],"absolute":[144],"(MAEs)":[146],"final":[149,175],"evaluated":[151],"independent":[154],"evaluation":[155],"0.795\u00b0C":[158],"2-hour":[161],"prediction,":[162,167],"1.485\u00b0C":[163],"6-hour":[166],"2.146\u00b0C":[169],"12-hour":[172,225],"prediction.":[173],"model":[176],"MAEs,":[177],"compared":[179],"research,":[183],"by":[186],"0.008\u00b0C,":[187],"0.081\u00b0C,":[188],"0.135\u00b0C,":[190],"respectively.":[191],"It":[192],"can":[193],"be":[194],"concluded":[195],"that":[196],"methods":[198],"used":[199],"research":[202],"effective":[204],"more":[206],"accurately":[207],"predicting":[208],"temperature.":[212],"different":[217],"periods":[219],"sequenced":[221],"provide":[223],"system":[230],"implementation":[232],"Georgia":[235],"Automated":[236],"Environmental":[237],"Monitoring":[238],"Network":[239],"website":[240],"(www.georgiaweather.net).":[241]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":3},{"year":2012,"cited_by_count":7}],"updated_date":"2026-08-06T08:24:18.245995","created_date":"2025-10-10T00:00:00"}
