{"id":"https://openalex.org/W4207038069","doi":"https://doi.org/10.1080/08839514.2022.2031823","title":"Hybrid Deep Learning-based Models for Crop Yield Prediction","display_name":"Hybrid Deep Learning-based Models for Crop Yield Prediction","publication_year":2022,"publication_date":"2022-01-22","ids":{"openalex":"https://openalex.org/W4207038069","doi":"https://doi.org/10.1080/08839514.2022.2031823"},"language":"en","primary_location":{"id":"doi:10.1080/08839514.2022.2031823","is_oa":true,"landing_page_url":"https://doi.org/10.1080/08839514.2022.2031823","pdf_url":"https://www.tandfonline.com/doi/epdf/10.1080/08839514.2022.2031823?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":true,"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":"other-oa","license_id":"https://openalex.org/licenses/other-oa","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":"gold","oa_url":"https://www.tandfonline.com/doi/epdf/10.1080/08839514.2022.2031823?needAccess=true&role=button","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5047358343","display_name":"Alexandros Oikonomidis","orcid":"https://orcid.org/0000-0003-4803-6419"},"institutions":[{"id":"https://openalex.org/I913481162","display_name":"Wageningen University & Research","ror":"https://ror.org/04qw24q55","country_code":"NL","type":"education","lineage":["https://openalex.org/I913481162"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Alexandros Oikonomidis","raw_affiliation_strings":["Information Technology Group, Wageningen University & Research, Wageningen, The Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Information Technology Group, Wageningen University & Research, Wageningen, The Netherlands","institution_ids":["https://openalex.org/I913481162"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038073619","display_name":"Cagatay Catal","orcid":"https://orcid.org/0000-0003-0959-2930"},"institutions":[{"id":"https://openalex.org/I60342839","display_name":"Qatar University","ror":"https://ror.org/00yhnba62","country_code":"QA","type":"education","lineage":["https://openalex.org/I60342839"]}],"countries":["QA"],"is_corresponding":true,"raw_author_name":"Cagatay Catal","raw_affiliation_strings":["Department of Computer Science and Engineering, Qatar University, Doha, Qatar"],"raw_orcid":"https://orcid.org/0000-0003-0959-2930","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Qatar University, Doha, Qatar","institution_ids":["https://openalex.org/I60342839"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060643121","display_name":"Ayalew Kassahun","orcid":null},"institutions":[{"id":"https://openalex.org/I913481162","display_name":"Wageningen University & Research","ror":"https://ror.org/04qw24q55","country_code":"NL","type":"education","lineage":["https://openalex.org/I913481162"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Ayalew Kassahun","raw_affiliation_strings":["Information Technology Group, Wageningen University & Research, Wageningen, The Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Information Technology Group, Wageningen University & Research, Wageningen, The Netherlands","institution_ids":["https://openalex.org/I913481162"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5038073619"],"corresponding_institution_ids":["https://openalex.org/I60342839"],"apc_list":{"value":2195,"currency":"USD","value_usd":2195},"apc_paid":{"value":2195,"currency":"USD","value_usd":2195},"fwci":32.5591,"has_fulltext":true,"cited_by_count":166,"citation_normalized_percentile":{"value":0.99846135,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"36","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9987999796867371,"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":0.9987999796867371,"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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9650999903678894,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12093","display_name":"Greenhouse Technology and Climate Control","score":0.9632999897003174,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8307157754898071},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6900207996368408},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.688953161239624},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6596298217773438},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.595409631729126},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.537388026714325},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5162248611450195},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.4565829634666443},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3440074920654297}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8307157754898071},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6900207996368408},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.688953161239624},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6596298217773438},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.595409631729126},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.537388026714325},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5162248611450195},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.4565829634666443},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3440074920654297},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1080/08839514.2022.2031823","is_oa":true,"landing_page_url":"https://doi.org/10.1080/08839514.2022.2031823","pdf_url":"https://www.tandfonline.com/doi/epdf/10.1080/08839514.2022.2031823?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":true,"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":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:26dfaad3676a4bc49b1ac12812e757ff","is_oa":true,"landing_page_url":"https://doaj.org/article/26dfaad3676a4bc49b1ac12812e757ff","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","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Applied Artificial Intelligence, Vol 36, Iss 1 (2022)","raw_type":"article"},{"id":"pmh:oai:figshare.com:article/25441756","is_oa":true,"landing_page_url":"https://figshare.com/articles/journal_contribution/Hybrid_Deep_Learning-based_Models_for_Crop_Yield_Prediction/25441756","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"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":"","raw_type":"Text"},{"id":"pmh:oai:qspace.qu.edu.qa:10576/36801","is_oa":false,"landing_page_url":"http://hdl.handle.net/10576/36801","pdf_url":null,"source":{"id":"https://openalex.org/S4306400014","display_name":"Qatar University QSpace (Qatar University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I60342839","host_organization_name":"Qatar University","host_organization_lineage":["https://openalex.org/I60342839"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Article"},{"id":"pmh:wur:oai:library.wur.nl:wurpubs/592804","is_oa":true,"landing_page_url":"https://research.wur.nl/en/publications/hybrid-deep-learning-based-models-for-crop-yield-prediction","pdf_url":null,"source":{"id":"https://openalex.org/S4306401843","display_name":"Data Archiving and Networked Services (DANS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1322597698","host_organization_name":"Royal Netherlands Academy of Arts and Sciences","host_organization_lineage":["https://openalex.org/I1322597698"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Applied artificial intelligence, 36(1), 1 - 18","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.1080/08839514.2022.2031823","is_oa":true,"landing_page_url":"https://doi.org/10.1080/08839514.2022.2031823","pdf_url":"https://www.tandfonline.com/doi/epdf/10.1080/08839514.2022.2031823?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":true,"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":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.5,"id":"https://metadata.un.org/sdg/2","display_name":"Zero hunger"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320334468","display_name":"Qatar National Library","ror":"https://ror.org/02jv93662"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4207038069.pdf","grobid_xml":"https://content.openalex.org/works/W4207038069.grobid-xml"},"referenced_works_count":40,"referenced_works":["https://openalex.org/W2072128103","https://openalex.org/W2107561290","https://openalex.org/W2251166296","https://openalex.org/W2412247133","https://openalex.org/W2543665758","https://openalex.org/W2567297430","https://openalex.org/W2604645045","https://openalex.org/W2805142011","https://openalex.org/W2896107488","https://openalex.org/W2902487926","https://openalex.org/W2910729503","https://openalex.org/W2914941211","https://openalex.org/W2919115771","https://openalex.org/W2922128523","https://openalex.org/W2945600159","https://openalex.org/W2949642792","https://openalex.org/W2979666105","https://openalex.org/W2980367889","https://openalex.org/W2982418982","https://openalex.org/W2987573763","https://openalex.org/W2992839153","https://openalex.org/W2996041315","https://openalex.org/W2997552745","https://openalex.org/W3007597990","https://openalex.org/W3009587349","https://openalex.org/W3011178959","https://openalex.org/W3014134514","https://openalex.org/W3015117847","https://openalex.org/W3015527879","https://openalex.org/W3017079270","https://openalex.org/W3020885311","https://openalex.org/W3029014910","https://openalex.org/W3034067006","https://openalex.org/W3042706118","https://openalex.org/W3043115696","https://openalex.org/W3079760979","https://openalex.org/W3099781968","https://openalex.org/W3123407900","https://openalex.org/W3177778236","https://openalex.org/W4255816075"],"related_works":["https://openalex.org/W4225394202","https://openalex.org/W4298287631","https://openalex.org/W2953061907","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W3008584592","https://openalex.org/W3167935049","https://openalex.org/W3029198973"],"abstract_inverted_index":{"Predicting":[0],"crop":[1],"yield":[2],"is":[3,29],"a":[4,98],"complex":[5],"task":[6],"since":[7],"it":[8],"depends":[9],"on":[10,97],"multiple":[11],"factors.":[12],"Although":[13],"many":[14],"models":[15,28,45],"have":[16],"been":[17],"developed":[18,42],"so":[19],"far":[20],"in":[21,62],"the":[22,24,49,66,91,119,144,159,170],"literature,":[23],"performance":[25,57],"of":[26,104,134,139,143,151],"current":[27],"not":[30],"satisfactory,":[31],"and":[32,84,109,112,136],"hence,":[33],"they":[34],"must":[35],"be":[36],"improved.":[37],"In":[38],"this":[39],"study,":[40,93],"we":[41,94],"deep":[43],"learning-based":[44],"to":[46,55,130,166,169],"evaluate":[47],"how":[48],"underlying":[50],"algorithms":[51,60],"perform":[52],"with":[53,147],"respect":[54],"different":[56],"criteria.":[58],"The":[59,115,141,153],"evaluated":[61],"our":[63],"study":[64],"are":[65],"XGBoost":[67,160],"machine":[68],"learning":[69],"(ML)":[70],"algorithm,":[71],"Convolutional":[72],"Neural":[73,76,81],"Networks":[74,77,82],"(CNN)-Deep":[75],"(DNN),":[78],"CNN-XGBoost,":[79],"CNN-Recurrent":[80],"(RNN),":[83],"CNN-Long":[85],"Short":[86],"Term":[87],"Memory":[88],"(LSTM).":[89],"For":[90],"case":[92],"performed":[95],"experiments":[96],"public":[99],"soybean":[100],"dataset":[101],"that":[102,118],"consists":[103],"395":[105],"features":[106],"including":[107],"weather":[108],"soil":[110],"parameters":[111],"25,345":[113],"samples.":[114],"results":[116],"showed":[117],"hybrid":[120],"CNN-DNN":[121],"model":[122,145],"outperforms":[123],"other":[124,171],"models,":[125],"having":[126],"an":[127,132,137,148],"RMSE":[128],"equal":[129],"0.266,":[131],"MSE":[133],"0.071,":[135],"MAE":[138],"0.199.":[140],"predictions":[142],"fit":[146],"R":[149],"2":[150],"0.87.":[152],"second-best":[154],"result":[155],"was":[156],"achieved":[157],"by":[158],"model,":[161],"which":[162],"required":[163],"less":[164],"time":[165],"execute":[167],"compared":[168],"DL-based":[172],"models.":[173]},"counts_by_year":[{"year":2026,"cited_by_count":11},{"year":2025,"cited_by_count":68},{"year":2024,"cited_by_count":52},{"year":2023,"cited_by_count":27},{"year":2022,"cited_by_count":8}],"updated_date":"2026-05-03T08:25:01.440150","created_date":"2025-10-10T00:00:00"}