{"id":"https://openalex.org/W4408384144","doi":"https://doi.org/10.1007/s42979-025-03778-9","title":"3TFL-XLnet-CP: A Novel Transformer-Based Crop Yield Prediction Framework with Weighted Loss Based 3-Tier Feature Learning Model","display_name":"3TFL-XLnet-CP: A Novel Transformer-Based Crop Yield Prediction Framework with Weighted Loss Based 3-Tier Feature Learning Model","publication_year":2025,"publication_date":"2025-03-12","ids":{"openalex":"https://openalex.org/W4408384144","doi":"https://doi.org/10.1007/s42979-025-03778-9"},"language":"en","primary_location":{"id":"doi:10.1007/s42979-025-03778-9","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s42979-025-03778-9","pdf_url":"https://link.springer.com/content/pdf/10.1007/s42979-025-03778-9.pdf","source":{"id":"https://openalex.org/S4210174798","display_name":"SN Computer Science","issn_l":"2661-8907","issn":["2661-8907","2662-995X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SN Computer Science","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s42979-025-03778-9.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5010933343","display_name":"G L Anoop","orcid":null},"institutions":[{"id":"https://openalex.org/I48018076","display_name":"Christ University","ror":"https://ror.org/022tv9y30","country_code":"IN","type":"education","lineage":["https://openalex.org/I48018076"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"G. L. Anoop","raw_affiliation_strings":["Department of Computer Science and Engineering, Christ University, Bengaluru, Karnataka, India"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Christ University, Bengaluru, Karnataka, India","institution_ids":["https://openalex.org/I48018076"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029228100","display_name":"C. Nandini","orcid":null},"institutions":[{"id":"https://openalex.org/I8977528","display_name":"Dr. Hari Singh Gour University","ror":"https://ror.org/01xapxe37","country_code":"IN","type":"education","lineage":["https://openalex.org/I8977528"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"C. Nandini","raw_affiliation_strings":["Department of Computer Science and Engineering, Dayananda Sagar Academy of Technology and Management, Bengaluru, Karnataka, India"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Dayananda Sagar Academy of Technology and Management, Bengaluru, Karnataka, India","institution_ids":["https://openalex.org/I8977528"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045294563","display_name":"E. Naresh","orcid":null},"institutions":[{"id":"https://openalex.org/I164861460","display_name":"Manipal Academy of Higher Education","ror":"https://ror.org/02xzytt36","country_code":"IN","type":"education","lineage":["https://openalex.org/I164861460"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"E. Naresh","raw_affiliation_strings":["Department of Information Technology, Manipal Institute of Technology Bengaluru, Manipal Academy of Higher Education, Manipal, India"],"affiliations":[{"raw_affiliation_string":"Department of Information Technology, Manipal Institute of Technology Bengaluru, Manipal Academy of Higher Education, Manipal, India","institution_ids":["https://openalex.org/I164861460"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5010933343"],"corresponding_institution_ids":["https://openalex.org/I48018076"],"apc_list":{"value":2290,"currency":"EUR","value_usd":2890},"apc_paid":{"value":2290,"currency":"EUR","value_usd":2890},"fwci":3.466,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.90671684,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":"6","issue":"3","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":0.9943000078201294,"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":0.9943000078201294,"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":0.9535999894142151,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5634520649909973},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5324360728263855},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4842042922973633},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.44590628147125244},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.44313207268714905},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3896864652633667},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.13568013906478882},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.05980983376502991}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5634520649909973},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5324360728263855},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4842042922973633},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44590628147125244},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.44313207268714905},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3896864652633667},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.13568013906478882},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.05980983376502991},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s42979-025-03778-9","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s42979-025-03778-9","pdf_url":"https://link.springer.com/content/pdf/10.1007/s42979-025-03778-9.pdf","source":{"id":"https://openalex.org/S4210174798","display_name":"SN Computer Science","issn_l":"2661-8907","issn":["2661-8907","2662-995X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SN Computer Science","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1007/s42979-025-03778-9","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s42979-025-03778-9","pdf_url":"https://link.springer.com/content/pdf/10.1007/s42979-025-03778-9.pdf","source":{"id":"https://openalex.org/S4210174798","display_name":"SN Computer Science","issn_l":"2661-8907","issn":["2661-8907","2662-995X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SN Computer Science","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4408384144.pdf"},"referenced_works_count":25,"referenced_works":["https://openalex.org/W2792091148","https://openalex.org/W2808964638","https://openalex.org/W2953686964","https://openalex.org/W2969691610","https://openalex.org/W3000098473","https://openalex.org/W3006608465","https://openalex.org/W3008924261","https://openalex.org/W3012717404","https://openalex.org/W3016913961","https://openalex.org/W3020885311","https://openalex.org/W3029014910","https://openalex.org/W3045041747","https://openalex.org/W3047228586","https://openalex.org/W3048168082","https://openalex.org/W3087070249","https://openalex.org/W3088885014","https://openalex.org/W3092639985","https://openalex.org/W3111174758","https://openalex.org/W3112881537","https://openalex.org/W3121715254","https://openalex.org/W3132602407","https://openalex.org/W3146049777","https://openalex.org/W3154229188","https://openalex.org/W3213239025","https://openalex.org/W4311081121"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4387369504","https://openalex.org/W3046775127","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W4364306694","https://openalex.org/W4312192474"],"abstract_inverted_index":{"Abstract":[0],"The":[1,66,85,151,167,188],"advancement":[2],"of":[3,92,193],"crop":[4,26,64,82,164,201],"yield":[5,27,165],"prediction":[6,83],"through":[7],"artificial":[8],"intelligence":[9],"(AI)":[10],"has":[11],"gained":[12],"significant":[13],"attention.":[14],"However,":[15],"the":[16,78,90,112,158,173,191],"existing":[17,179],"AI-based":[18],"approaches":[19],"for":[20,161],"maximizing":[21],"agricultural":[22,59],"productivity,":[23],"specifically":[24],"in":[25,75,198],"prediction,":[28],"have":[29],"not":[30],"consistently":[31],"delivered":[32],"satisfactory":[33],"results.":[34],"In":[35],"response":[36],"to":[37,106,124,136],"this":[38],"challenge,":[39],"we":[40],"propose":[41],"a":[42,70,130,143],"novel":[43,144],"framework":[44,68,197],"named":[45],"as":[46,182],"Three":[47],"Tier":[48],"Feature":[49],"Learning":[50],"with":[51,77],"XLnet":[52,80],"based":[53],"Crop":[54],"Prediction":[55],"(3TFL-XLnet-CP)":[56],"that":[57],"enhances":[58],"productivity":[60],"by":[61,142],"accurately":[62,199],"predicting":[63,200],"yield.":[65,202],"3TFL-XLnet-CP":[67,196],"employs":[69],"three-tier":[71,86],"feature":[72,87,109,116,138],"learning":[73,88],"approach":[74],"combination":[76],"powerful":[79],"transformer-based":[81],"model.":[84],"involves":[89],"integration":[91],"Spiking":[93],"Neural":[94,98,103],"Network":[95,99,104],"(SNN),":[96],"Graphical":[97],"(GNN),":[100],"and":[101,176,186],"Convolutional":[102],"(CNN)":[105],"extract":[107],"distinct":[108],"vectors":[110,117],"from":[111],"preprocessed":[113],"data.":[114],"These":[115],"are":[118,154],"then":[119],"concatenated":[120,152],"using":[121,172],"Jaccard":[122],"Similarity":[123],"measure":[125],"their":[126],"similarity":[127],"score.":[128],"Additionally,":[129],"weighted":[131],"Loss":[132],"function":[133],"is":[134,170],"introduced":[135],"optimize":[137],"learning,":[139],"further":[140],"enhanced":[141],"self-adaptive":[145],"Spider":[146],"Monkey":[147],"Optimization":[148],"algorithm":[149],"(SASMO).":[150],"features":[153],"subsequently":[155],"fed":[156],"into":[157],"classification":[159],"layer":[160],"making":[162],"precise":[163],"predictions.":[166],"proposed":[168,195],"model":[169],"implemented":[171],"Python":[174],"platform":[175],"evaluated":[177],"against":[178],"models":[180],"such":[181],"ANN,":[183],"RNN,":[184],"DNN,":[185],"BiLSTM.":[187],"comparison":[189],"demonstrates":[190],"superiority":[192],"our":[194]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-04-01T17:29:45.350535","created_date":"2025-10-10T00:00:00"}
