{"id":"https://openalex.org/W4412605231","doi":"https://doi.org/10.1109/access.2025.3591802","title":"A Stacking Ensemble Framework Leveraging Synthetic Data for Accurate and Stable Crop Yield Forecasting","display_name":"A Stacking Ensemble Framework Leveraging Synthetic Data for Accurate and Stable Crop Yield Forecasting","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4412605231","doi":"https://doi.org/10.1109/access.2025.3591802"},"language":"en","primary_location":{"id":"doi:10.1109/access.2025.3591802","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3591802","pdf_url":null,"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://doi.org/10.1109/access.2025.3591802","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102004099","display_name":"Muhammad Waqar","orcid":"https://orcid.org/0009-0002-8413-2926"},"institutions":[{"id":"https://openalex.org/I83202590","display_name":"Jeju National University","ror":"https://ror.org/05hnb4n85","country_code":"KR","type":"education","lineage":["https://openalex.org/I83202590"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Muhammad Waqar","raw_affiliation_strings":["Department of Electronic Engineering, Institute of Information Science and Technology, Jeju National University, Jeju-si, South Korea"],"raw_orcid":"https://orcid.org/0009-0002-8413-2926","affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Institute of Information Science and Technology, Jeju National University, Jeju-si, South Korea","institution_ids":["https://openalex.org/I83202590"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050487609","display_name":"Yong\u2010Woon Kim","orcid":"https://orcid.org/0000-0002-4759-0138"},"institutions":[{"id":"https://openalex.org/I83202590","display_name":"Jeju National University","ror":"https://ror.org/05hnb4n85","country_code":"KR","type":"education","lineage":["https://openalex.org/I83202590"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Yong-Woon Kim","raw_affiliation_strings":["Department of Computer Engineering, Jeju National University, Jeju-si, South Korea"],"raw_orcid":"https://orcid.org/0000-0002-4759-0138","affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Jeju National University, Jeju-si, South Korea","institution_ids":["https://openalex.org/I83202590"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110809957","display_name":"Yung-Cheol Byun","orcid":"https://orcid.org/0000-0003-1107-9941"},"institutions":[{"id":"https://openalex.org/I83202590","display_name":"Jeju National University","ror":"https://ror.org/05hnb4n85","country_code":"KR","type":"education","lineage":["https://openalex.org/I83202590"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Yung-Cheol Byun","raw_affiliation_strings":["Department of Computer Engineering (Major of Electronic Engineering), Institute of Information Science and Technology, Jeju National University, Jeju-si, South Korea"],"raw_orcid":"https://orcid.org/0000-0003-1107-9941","affiliations":[{"raw_affiliation_string":"Department of Computer Engineering (Major of Electronic Engineering), Institute of Information Science and Technology, Jeju National University, Jeju-si, South Korea","institution_ids":["https://openalex.org/I83202590"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I83202590"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":9.5569,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.98050424,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":100},"biblio":{"volume":"13","issue":null,"first_page":"136909","last_page":"136926"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.767799973487854,"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"}},"topics":[{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.767799973487854,"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/T11052","display_name":"Energy Load and Power Forecasting","score":0.7010999917984009,"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"}},{"id":"https://openalex.org/T12368","display_name":"Grey System Theory Applications","score":0.6593999862670898,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/yield","display_name":"Yield (engineering)","score":0.6643306612968445},{"id":"https://openalex.org/keywords/stacking","display_name":"Stacking","score":0.6480275392532349},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6389662027359009},{"id":"https://openalex.org/keywords/crop-yield","display_name":"Crop yield","score":0.5046299695968628},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.45658841729164124},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3705894649028778},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3445020318031311},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32963675260543823},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.09795942902565002},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.09547275304794312},{"id":"https://openalex.org/keywords/agronomy","display_name":"Agronomy","score":0.09385707974433899}],"concepts":[{"id":"https://openalex.org/C134121241","wikidata":"https://www.wikidata.org/wiki/Q899301","display_name":"Yield (engineering)","level":2,"score":0.6643306612968445},{"id":"https://openalex.org/C33347731","wikidata":"https://www.wikidata.org/wiki/Q285210","display_name":"Stacking","level":2,"score":0.6480275392532349},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6389662027359009},{"id":"https://openalex.org/C126343540","wikidata":"https://www.wikidata.org/wiki/Q889514","display_name":"Crop yield","level":2,"score":0.5046299695968628},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.45658841729164124},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3705894649028778},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3445020318031311},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32963675260543823},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.09795942902565002},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.09547275304794312},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.09385707974433899},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C191897082","wikidata":"https://www.wikidata.org/wiki/Q11467","display_name":"Metallurgy","level":1,"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/C46141821","wikidata":"https://www.wikidata.org/wiki/Q209402","display_name":"Nuclear magnetic resonance","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2025.3591802","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3591802","pdf_url":null,"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:2a4bcf18e64e41269c61037d96343a04","is_oa":true,"landing_page_url":"https://doaj.org/article/2a4bcf18e64e41269c61037d96343a04","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 13, Pp 136909-136926 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2025.3591802","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3591802","pdf_url":null,"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":[{"id":"https://metadata.un.org/sdg/2","display_name":"Zero hunger","score":0.7599999904632568}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":57,"referenced_works":["https://openalex.org/W317957491","https://openalex.org/W1536719639","https://openalex.org/W2059700429","https://openalex.org/W2296609147","https://openalex.org/W3037618930","https://openalex.org/W3039924663","https://openalex.org/W3045041747","https://openalex.org/W3047562107","https://openalex.org/W3112881537","https://openalex.org/W3127209611","https://openalex.org/W3135855863","https://openalex.org/W3142740975","https://openalex.org/W3159526010","https://openalex.org/W3174086521","https://openalex.org/W3177848562","https://openalex.org/W3182706339","https://openalex.org/W3183713831","https://openalex.org/W3214033107","https://openalex.org/W3214840804","https://openalex.org/W3216316500","https://openalex.org/W4207038069","https://openalex.org/W4225556963","https://openalex.org/W4280504305","https://openalex.org/W4280618660","https://openalex.org/W4285464468","https://openalex.org/W4293086963","https://openalex.org/W4293372980","https://openalex.org/W4301229630","https://openalex.org/W4307044600","https://openalex.org/W4307093192","https://openalex.org/W4318559729","https://openalex.org/W4361276701","https://openalex.org/W4366742679","https://openalex.org/W4367333180","https://openalex.org/W4384819716","https://openalex.org/W4385878916","https://openalex.org/W4387197185","https://openalex.org/W4387350610","https://openalex.org/W4390421206","https://openalex.org/W4392909547","https://openalex.org/W4392990349","https://openalex.org/W4393307099","https://openalex.org/W4395463236","https://openalex.org/W4398774912","https://openalex.org/W4400112726","https://openalex.org/W4402592871","https://openalex.org/W4403214784","https://openalex.org/W4403942018","https://openalex.org/W4406188277","https://openalex.org/W4406259676","https://openalex.org/W4407449754","https://openalex.org/W4408196902","https://openalex.org/W4411055467","https://openalex.org/W6845642338","https://openalex.org/W6861145305","https://openalex.org/W6876224237","https://openalex.org/W6912065386"],"related_works":["https://openalex.org/W2035329725","https://openalex.org/W2070875936","https://openalex.org/W4250391473","https://openalex.org/W4302292679","https://openalex.org/W4241625287","https://openalex.org/W2050788868","https://openalex.org/W4295885776","https://openalex.org/W2027634686","https://openalex.org/W3036164038","https://openalex.org/W1546742213"],"abstract_inverted_index":{"With":[0],"the":[1,52,76,141,146],"rapid":[2],"increase":[3],"in":[4],"world\u2019s":[5],"population":[6],"and":[7,21,37,64,82,93,102,113,124,130,136,143],"changing":[8],"climate":[9],"patterns,":[10],"accurate":[11],"crop":[12,104,151],"yield":[13,28,152],"forecasting":[14],"is":[15],"essential":[16],"to":[17,89],"ensure":[18],"food":[19],"security":[20],"sustainable":[22],"agriculture.":[23],"This":[24],"study":[25],"presents":[26],"a":[27],"prediction":[29],"framework":[30],"consisting":[31],"of":[32,145],"Stacking":[33],"Ensemble":[34],"Model":[35],"(SEM)":[36],"its":[38],"Optimized":[39],"variant":[40],"(OSEM),":[41],"which":[42],"integrates":[43],"real-world":[44],"agricultural":[45],"data":[46,49],"with":[47,70],"synthetic":[48],"generated":[50],"using":[51,85],"Prophet":[53],"time-series":[54],"model.":[55],"The":[56],"ensemble":[57],"comprises":[58],"Random":[59],"Forest,":[60],"XGBoost,":[61],"Decision":[62],"Tree,":[63],"K-Nearest":[65],"Neighbors":[66],"as":[67,75],"base":[68],"learners,":[69],"an":[71],"Extra":[72],"Trees":[73],"Regressor":[74],"meta-learner.":[77],"OSEM":[78,108],"incorporates":[79],"hyperparameter":[80],"tuning":[81],"dimensionality":[83],"reduction":[84],"Singular":[86],"Value":[87],"Decomposition":[88],"enhance":[90],"predictive":[91],"performance":[92],"reduce":[94],"feature":[95],"noise.":[96],"Extensive":[97],"experiments":[98],"on":[99],"globally":[100],"distributed":[101],"region-specific":[103],"datasets":[105],"demonstrate":[106],"that":[107],"consistently":[109],"outperforms":[110],"both":[111],"SEM":[112],"state-of-the-art":[114],"baselines,":[115],"achieving":[116],"<italic":[117],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[118,120],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">R</i><sup":[119],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">2</sup>":[121],"=":[122,126],"0.996":[123],"MAE":[125],"0.185":[127],"t/ha.":[128],"Stability":[129],"convergence":[131],"analysis,":[132],"supported":[133],"by":[134],"Wilcoxon":[135],"Friedman":[137],"tests,":[138],"further":[139],"confirm":[140],"robustness":[142],"reliability":[144],"proposed":[147],"model":[148],"for":[149],"scalable":[150],"forecasting.":[153]},"counts_by_year":[{"year":2026,"cited_by_count":8},{"year":2025,"cited_by_count":2}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}