{"id":"https://openalex.org/W2972684407","doi":"https://doi.org/10.1109/access.2019.2940266","title":"Forecasting of Grain Pile Temperature From Meteorological Factors Using Machine Learning","display_name":"Forecasting of Grain Pile Temperature From Meteorological Factors Using Machine Learning","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2972684407","doi":"https://doi.org/10.1109/access.2019.2940266","mag":"2972684407"},"language":"en","primary_location":{"id":"doi:10.1109/access.2019.2940266","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2940266","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08832145.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08832145.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5065289838","display_name":"Shanshan Duan","orcid":"https://orcid.org/0000-0002-7225-4232"},"institutions":[{"id":"https://openalex.org/I36152291","display_name":"Henan University of Technology","ror":"https://ror.org/05sbgwt55","country_code":"CN","type":"education","lineage":["https://openalex.org/I36152291"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shanshan Duan","raw_affiliation_strings":["College of Information Science and Engineering, Henan University of Technology, Zhengzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Science and Engineering, Henan University of Technology, Zhengzhou, China","institution_ids":["https://openalex.org/I36152291"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101865876","display_name":"Weidong Yang","orcid":"https://orcid.org/0000-0003-3105-5269"},"institutions":[{"id":"https://openalex.org/I36152291","display_name":"Henan University of Technology","ror":"https://ror.org/05sbgwt55","country_code":"CN","type":"education","lineage":["https://openalex.org/I36152291"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weidong Yang","raw_affiliation_strings":["College of Information Science and Engineering, Henan University of Technology, Zhengzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Science and Engineering, Henan University of Technology, Zhengzhou, China","institution_ids":["https://openalex.org/I36152291"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043788836","display_name":"Xuyu Wang","orcid":"https://orcid.org/0000-0002-4759-8674"},"institutions":[{"id":"https://openalex.org/I43522216","display_name":"California State University, Sacramento","ror":"https://ror.org/03e26wv14","country_code":"US","type":"education","lineage":["https://openalex.org/I43522216"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xuyu Wang","raw_affiliation_strings":["Department of Computer Science, California State University, Sacramento, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, California State University, Sacramento, CA, USA","institution_ids":["https://openalex.org/I43522216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080122431","display_name":"Shiwen Mao","orcid":"https://orcid.org/0000-0002-7052-0007"},"institutions":[{"id":"https://openalex.org/I82497590","display_name":"Auburn University","ror":"https://ror.org/02v80fc35","country_code":"US","type":"education","lineage":["https://openalex.org/I82497590"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shiwen Mao","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Auburn University, Auburn, AL, USA"],"raw_orcid":"https://orcid.org/0000-0002-7052-0007","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Auburn University, Auburn, AL, USA","institution_ids":["https://openalex.org/I82497590"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100368699","display_name":"Yuan Zhang","orcid":"https://orcid.org/0000-0002-3225-2769"},"institutions":[{"id":"https://openalex.org/I36152291","display_name":"Henan University of Technology","ror":"https://ror.org/05sbgwt55","country_code":"CN","type":"education","lineage":["https://openalex.org/I36152291"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuan Zhang","raw_affiliation_strings":["College of Information Science and Engineering, Henan University of Technology, Zhengzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Science and Engineering, Henan University of Technology, Zhengzhou, China","institution_ids":["https://openalex.org/I36152291"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.1964,"has_fulltext":true,"cited_by_count":28,"citation_normalized_percentile":{"value":0.77374229,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"7","issue":null,"first_page":"130721","last_page":"130733"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.980400025844574,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.980400025844574,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9724000096321106,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9659000039100647,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/adaboost","display_name":"AdaBoost","score":0.6675708889961243},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.5719963312149048},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5717030763626099},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5575305223464966},{"id":"https://openalex.org/keywords/granary","display_name":"Granary","score":0.5477950572967529},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.5434967875480652},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.5058481693267822},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.478208065032959},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.44989365339279175},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4088987410068512},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40387219190597534},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2793928384780884},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21962210536003113},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.1922946572303772},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.08083486557006836}],"concepts":[{"id":"https://openalex.org/C141404830","wikidata":"https://www.wikidata.org/wiki/Q2823869","display_name":"AdaBoost","level":3,"score":0.6675708889961243},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.5719963312149048},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5717030763626099},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5575305223464966},{"id":"https://openalex.org/C2776370464","wikidata":"https://www.wikidata.org/wiki/Q114768","display_name":"Granary","level":2,"score":0.5477950572967529},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.5434967875480652},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.5058481693267822},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.478208065032959},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.44989365339279175},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4088987410068512},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40387219190597534},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2793928384780884},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21962210536003113},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.1922946572303772},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.08083486557006836},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2019.2940266","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2940266","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08832145.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:d187862278974f4daa486182bd2979f9","is_oa":true,"landing_page_url":"https://doaj.org/article/d187862278974f4daa486182bd2979f9","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 7, Pp 130721-130733 (2019)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2019.2940266","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2940266","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08832145.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.6399999856948853,"id":"https://metadata.un.org/sdg/2","display_name":"Zero hunger"}],"awards":[{"id":"https://openalex.org/G1508479062","display_name":"WiFiUS: RF Sensing in Internet of Things: When Deep Learning Meets CSI Tensor","funder_award_id":"1702957","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G1576385751","display_name":null,"funder_award_id":"CNS-1702957","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G3337278731","display_name":null,"funder_award_id":"2017YFD0401003","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320309904","display_name":"Auburn University","ror":"https://ror.org/02v80fc35"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2972684407.pdf","grobid_xml":"https://content.openalex.org/works/W2972684407.grobid-xml"},"referenced_works_count":52,"referenced_works":["https://openalex.org/W1718586316","https://openalex.org/W1923027492","https://openalex.org/W1964077055","https://openalex.org/W1964357740","https://openalex.org/W1966251282","https://openalex.org/W1981801027","https://openalex.org/W1987676247","https://openalex.org/W2005424446","https://openalex.org/W2011666252","https://openalex.org/W2031180132","https://openalex.org/W2032776072","https://openalex.org/W2033275656","https://openalex.org/W2034775355","https://openalex.org/W2042182710","https://openalex.org/W2042230250","https://openalex.org/W2046173641","https://openalex.org/W2054919690","https://openalex.org/W2062689570","https://openalex.org/W2065819440","https://openalex.org/W2069262928","https://openalex.org/W2075854397","https://openalex.org/W2295124130","https://openalex.org/W2345272516","https://openalex.org/W2368496171","https://openalex.org/W2510733152","https://openalex.org/W2586707960","https://openalex.org/W2589643792","https://openalex.org/W2593995123","https://openalex.org/W2605165679","https://openalex.org/W2726014691","https://openalex.org/W2742840809","https://openalex.org/W2775545376","https://openalex.org/W2780110639","https://openalex.org/W2790103198","https://openalex.org/W2806317011","https://openalex.org/W2887113932","https://openalex.org/W2897716041","https://openalex.org/W2898326364","https://openalex.org/W2901044800","https://openalex.org/W2901107889","https://openalex.org/W2904468728","https://openalex.org/W2914178424","https://openalex.org/W2948743652","https://openalex.org/W2962748597","https://openalex.org/W2978737999","https://openalex.org/W3125965402","https://openalex.org/W6637601825","https://openalex.org/W6733758009","https://openalex.org/W6736163905","https://openalex.org/W6747314434","https://openalex.org/W6762717648","https://openalex.org/W6768848096"],"related_works":["https://openalex.org/W2579148721","https://openalex.org/W3211783303","https://openalex.org/W4387893611","https://openalex.org/W2347335694","https://openalex.org/W2091056927","https://openalex.org/W2067407580","https://openalex.org/W2052828961","https://openalex.org/W4317486777","https://openalex.org/W2166180245","https://openalex.org/W2376566779"],"abstract_inverted_index":{"Food":[0],"storage":[1],"security":[2],"is":[3],"critical":[4],"to":[5,24,40,71,75,163],"the":[6,60,77,81,106,111,115,120,126,136,139,146,169,180,193,202,210],"national":[7],"economy":[8],"and":[9,42,58,94,109,114,138,178,184,201],"people's":[10],"lives.":[11],"The":[12,189],"environmental":[13],"parameters":[14],"of":[15,50,80,117,132,171],"a":[16,26,48,54,88,129,198],"granary":[17,137],"should":[18],"be":[19],"accurately":[20],"monitored":[21],"in":[22,105,119],"order":[23,162],"provide":[25],"better":[27],"preservation":[28],"environment":[29],"for":[30,47],"food":[31],"storage.":[32],"In":[33,161],"this":[34],"paper,":[35],"we":[36,167],"use":[37],"temperature":[38,45,79],"sensors":[39],"measure":[41],"collect":[43,59],"grain":[44,82],"data":[46,63,74,134,143,172],"period":[49],"423":[51],"days":[52],"from":[53,64,135],"real":[55],"world":[56],"granary,":[57],"corresponding":[61,140],"meteorological":[62,73,141,159],"China":[65],"Meteorological":[66],"Data":[67],"Network.":[68],"We":[69,100,123,150],"propose":[70],"leverage":[72],"predict":[76],"average":[78],"pile":[83],"with":[84],"machine":[85],"learning":[86],"algorithms:":[87],"support":[89],"vector":[90],"regression":[91],"(SVR)":[92],"approach":[93],"an":[95],"adaptive":[96],"boosting":[97],"(AdaBoost)":[98],"approach.":[99],"incorporate":[101],"different":[102],"kernel":[103],"functions":[104],"SVR":[107],"model":[108],"choose":[110],"appropriate":[112],"base-estimator":[113],"number":[116],"estimators":[118],"AdaBoost":[121],"model.":[122],"then":[124],"analyze":[125],"correlation":[127,148],"between":[128,157],"large":[130],"amount":[131],"historical":[133],"forecast":[142],"based":[144],"on":[145],"Pearson":[147],"coefficient.":[149],"find":[151],"that":[152,192],"there":[153],"are":[154],"strong":[155],"correlations":[156],"some":[158],"factors.":[160],"eliminate":[164],"redundant":[165],"information,":[166],"reduce":[168],"dimension":[170,187,207],"by":[173],"principal":[174],"components":[175],"analysis":[176],"(PCA),":[177],"compare":[179],"prediction":[181],"models":[182],"before":[183],"after":[185,205],"PCA":[186,206],"reduction.":[188],"results":[190],"show":[191],"proposed":[194],"approaches":[195],"can":[196],"achieve":[197],"high":[199],"accuracy":[200],"Adboost":[203],"method":[204],"reduction":[208],"achieves":[209],"best":[211],"performance.":[212]},"counts_by_year":[{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":5}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}