{"id":"https://openalex.org/W7154936515","doi":"https://doi.org/10.1016/j.asoc.2026.115278","title":"A novel multi-modal dynamic integration model for carbon price prediction considering data distribution feature drift and optimal diverse base model set","display_name":"A novel multi-modal dynamic integration model for carbon price prediction considering data distribution feature drift and optimal diverse base model set","publication_year":2026,"publication_date":"2026-04-20","ids":{"openalex":"https://openalex.org/W7154936515","doi":"https://doi.org/10.1016/j.asoc.2026.115278"},"language":"en","primary_location":{"id":"doi:10.1016/j.asoc.2026.115278","is_oa":false,"landing_page_url":"https://doi.org/10.1016/j.asoc.2026.115278","pdf_url":null,"source":{"id":"https://openalex.org/S140556538","display_name":"Applied Soft Computing","issn_l":"1568-4946","issn":["1568-4946","1872-9681"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Soft Computing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5037725197","display_name":"Maolin He","orcid":"https://orcid.org/0000-0002-1017-9724"},"institutions":[{"id":"https://openalex.org/I200845125","display_name":"Nanjing University of Information Science and Technology","ror":"https://ror.org/02y0rxk19","country_code":"CN","type":"education","lineage":["https://openalex.org/I200845125"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Maolin He","raw_affiliation_strings":["School of Management Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China"],"raw_orcid":"https://orcid.org/0000-0002-1017-9724","affiliations":[{"raw_affiliation_string":"School of Management Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China","institution_ids":["https://openalex.org/I200845125"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5134039094","display_name":"Jujie Wang","orcid":"https://orcid.org/0000-0003-0574-5661"},"institutions":[{"id":"https://openalex.org/I200845125","display_name":"Nanjing University of Information Science and Technology","ror":"https://ror.org/02y0rxk19","country_code":"CN","type":"education","lineage":["https://openalex.org/I200845125"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jujie Wang","raw_affiliation_strings":["School of Management Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China"],"raw_orcid":"https://orcid.org/0000-0003-0574-5661","affiliations":[{"raw_affiliation_string":"School of Management Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China","institution_ids":["https://openalex.org/I200845125"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5134039094"],"corresponding_institution_ids":["https://openalex.org/I200845125"],"apc_list":{"value":3350,"currency":"USD","value_usd":3350},"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.55669984,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"198","issue":null,"first_page":"115278","last_page":"115278"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.29120001196861267,"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"}},"topics":[{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.29120001196861267,"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"}},{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":0.2517000138759613,"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/T11918","display_name":"Forecasting Techniques and Applications","score":0.08250000327825546,"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/weighting","display_name":"Weighting","score":0.6212000250816345},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5899999737739563},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.47940000891685486},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.46650001406669617},{"id":"https://openalex.org/keywords/concept-drift","display_name":"Concept drift","score":0.40540000796318054},{"id":"https://openalex.org/keywords/base","display_name":"Base (topology)","score":0.3785000145435333},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.3659999966621399},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.350600004196167}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7232999801635742},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.6212000250816345},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5899999737739563},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.47940000891685486},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.46650001406669617},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4643000066280365},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4138000011444092},{"id":"https://openalex.org/C60777511","wikidata":"https://www.wikidata.org/wiki/Q3045002","display_name":"Concept drift","level":3,"score":0.40540000796318054},{"id":"https://openalex.org/C42058472","wikidata":"https://www.wikidata.org/wiki/Q810214","display_name":"Base (topology)","level":2,"score":0.3785000145435333},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.3659999966621399},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.350600004196167},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.32580000162124634},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.311599999666214},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.310699999332428},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.3084999918937683},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.30730000138282776},{"id":"https://openalex.org/C119898033","wikidata":"https://www.wikidata.org/wiki/Q3433888","display_name":"Ensemble forecasting","level":2,"score":0.3012999892234802},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.2922999858856201},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.29179999232292175},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.29100000858306885},{"id":"https://openalex.org/C197298091","wikidata":"https://www.wikidata.org/wiki/Q5318963","display_name":"Dynamic data","level":2,"score":0.2667999863624573},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.26269999146461487},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.2612000107765198},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.25619998574256897}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1016/j.asoc.2026.115278","is_oa":false,"landing_page_url":"https://doi.org/10.1016/j.asoc.2026.115278","pdf_url":null,"source":{"id":"https://openalex.org/S140556538","display_name":"Applied Soft Computing","issn_l":"1568-4946","issn":["1568-4946","1872-9681"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Soft Computing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":56,"referenced_works":["https://openalex.org/W307184769","https://openalex.org/W2000982976","https://openalex.org/W2060629445","https://openalex.org/W2064675550","https://openalex.org/W2116661285","https://openalex.org/W2265008683","https://openalex.org/W2288054910","https://openalex.org/W2484979138","https://openalex.org/W2622999711","https://openalex.org/W2890866454","https://openalex.org/W2896532220","https://openalex.org/W2904390847","https://openalex.org/W2908061993","https://openalex.org/W2913219845","https://openalex.org/W2975108999","https://openalex.org/W2979028505","https://openalex.org/W2989940830","https://openalex.org/W2990474957","https://openalex.org/W2990569776","https://openalex.org/W2997833886","https://openalex.org/W3004627076","https://openalex.org/W3005888476","https://openalex.org/W3016462384","https://openalex.org/W3039014617","https://openalex.org/W3159573745","https://openalex.org/W3199619828","https://openalex.org/W3216736957","https://openalex.org/W4200496819","https://openalex.org/W4210545146","https://openalex.org/W4213265320","https://openalex.org/W4280507065","https://openalex.org/W4283460176","https://openalex.org/W4283758841","https://openalex.org/W4285992182","https://openalex.org/W4287448629","https://openalex.org/W4292266167","https://openalex.org/W4295278393","https://openalex.org/W4303579761","https://openalex.org/W4307939667","https://openalex.org/W4313319964","https://openalex.org/W4320489593","https://openalex.org/W4376651320","https://openalex.org/W4381951332","https://openalex.org/W4383497689","https://openalex.org/W4388594187","https://openalex.org/W4390569801","https://openalex.org/W4390848533","https://openalex.org/W4391203570","https://openalex.org/W4393999162","https://openalex.org/W4403997341","https://openalex.org/W4405365912","https://openalex.org/W4405807941","https://openalex.org/W4406255379","https://openalex.org/W4406382370","https://openalex.org/W4406713749","https://openalex.org/W4406933822"],"related_works":[],"abstract_inverted_index":null,"counts_by_year":[],"updated_date":"2026-06-15T08:34:33.830935","created_date":"2026-04-21T00:00:00"}
