{"id":"https://openalex.org/W2883615841","doi":"https://doi.org/10.3390/info9070177","title":"A Hybrid Model for Monthly Precipitation Time Series Forecasting Based on Variational Mode Decomposition with Extreme Learning Machine","display_name":"A Hybrid Model for Monthly Precipitation Time Series Forecasting Based on Variational Mode Decomposition with Extreme Learning Machine","publication_year":2018,"publication_date":"2018-07-20","ids":{"openalex":"https://openalex.org/W2883615841","doi":"https://doi.org/10.3390/info9070177","mag":"2883615841"},"language":"en","primary_location":{"id":"doi:10.3390/info9070177","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info9070177","pdf_url":"https://www.mdpi.com/2078-2489/9/7/177/pdf?version=1532069693","source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Information","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2078-2489/9/7/177/pdf?version=1532069693","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100337868","display_name":"Guohui Li","orcid":"https://orcid.org/0000-0001-8175-4311"},"institutions":[{"id":"https://openalex.org/I4210136859","display_name":"Xi\u2019an University of Posts and Telecommunications","ror":"https://ror.org/04jn0td46","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136859"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Guohui Li","raw_affiliation_strings":["School of Electronic Engineering, Xi\u2019an University of Posts and Telecommunications, Xi\u2019an 710121, China","School of Electronic Engineering, Xi'an University of Posts and Telecommunications, Xi'an 710121, China"],"raw_orcid":"https://orcid.org/0000-0001-8175-4311","affiliations":[{"raw_affiliation_string":"School of Electronic Engineering, Xi\u2019an University of Posts and Telecommunications, Xi\u2019an 710121, China","institution_ids":["https://openalex.org/I4210136859"]},{"raw_affiliation_string":"School of Electronic Engineering, Xi'an University of Posts and Telecommunications, Xi'an 710121, China","institution_ids":["https://openalex.org/I4210136859"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020323895","display_name":"Xiao Ma","orcid":"https://orcid.org/0000-0003-1017-9481"},"institutions":[{"id":"https://openalex.org/I4210136859","display_name":"Xi\u2019an University of Posts and Telecommunications","ror":"https://ror.org/04jn0td46","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136859"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiao Ma","raw_affiliation_strings":["School of Electronic Engineering, Xi\u2019an University of Posts and Telecommunications, Xi\u2019an 710121, China","School of Electronic Engineering, Xi'an University of Posts and Telecommunications, Xi'an 710121, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic Engineering, Xi\u2019an University of Posts and Telecommunications, Xi\u2019an 710121, China","institution_ids":["https://openalex.org/I4210136859"]},{"raw_affiliation_string":"School of Electronic Engineering, Xi'an University of Posts and Telecommunications, Xi'an 710121, China","institution_ids":["https://openalex.org/I4210136859"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062896696","display_name":"Hong Yang","orcid":"https://orcid.org/0000-0002-7028-5879"},"institutions":[{"id":"https://openalex.org/I4210136859","display_name":"Xi\u2019an University of Posts and Telecommunications","ror":"https://ror.org/04jn0td46","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136859"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hong Yang","raw_affiliation_strings":["School of Electronic Engineering, Xi\u2019an University of Posts and Telecommunications, Xi\u2019an 710121, China","School of Electronic Engineering, Xi'an University of Posts and Telecommunications, Xi'an 710121, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic Engineering, Xi\u2019an University of Posts and Telecommunications, Xi\u2019an 710121, China","institution_ids":["https://openalex.org/I4210136859"]},{"raw_affiliation_string":"School of Electronic Engineering, Xi'an University of Posts and Telecommunications, Xi'an 710121, China","institution_ids":["https://openalex.org/I4210136859"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5062896696","https://openalex.org/A5100337868"],"corresponding_institution_ids":["https://openalex.org/I4210136859"],"apc_list":{"value":1400,"currency":"CHF","value_usd":1515},"apc_paid":{"value":1400,"currency":"CHF","value_usd":1515},"fwci":1.8809,"has_fulltext":true,"cited_by_count":35,"citation_normalized_percentile":{"value":0.83636301,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"9","issue":"7","first_page":"177","last_page":"177"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11490","display_name":"Hydrological Forecasting Using AI","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11490","display_name":"Hydrological Forecasting Using AI","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental 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":0.9988999962806702,"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/T12676","display_name":"Machine Learning and ELM","score":0.9975000023841858,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/extreme-learning-machine","display_name":"Extreme learning machine","score":0.8800926208496094},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.7282294034957886},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6739316582679749},{"id":"https://openalex.org/keywords/mean-absolute-percentage-error","display_name":"Mean absolute percentage error","score":0.6093856692314148},{"id":"https://openalex.org/keywords/precipitation","display_name":"Precipitation","score":0.5884768962860107},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5300977826118469},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5225581526756287},{"id":"https://openalex.org/keywords/mode","display_name":"Mode (computer interface)","score":0.5075701475143433},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.454316109418869},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.3874499499797821},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33607202768325806},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.32685112953186035},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.30872976779937744},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.27385422587394714},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.08243998885154724},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.08154746890068054}],"concepts":[{"id":"https://openalex.org/C2780150128","wikidata":"https://www.wikidata.org/wiki/Q21948731","display_name":"Extreme learning machine","level":3,"score":0.8800926208496094},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.7282294034957886},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6739316582679749},{"id":"https://openalex.org/C150217764","wikidata":"https://www.wikidata.org/wiki/Q6803607","display_name":"Mean absolute percentage error","level":3,"score":0.6093856692314148},{"id":"https://openalex.org/C107054158","wikidata":"https://www.wikidata.org/wiki/Q25257","display_name":"Precipitation","level":2,"score":0.5884768962860107},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5300977826118469},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5225581526756287},{"id":"https://openalex.org/C48677424","wikidata":"https://www.wikidata.org/wiki/Q6888088","display_name":"Mode (computer interface)","level":2,"score":0.5075701475143433},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.454316109418869},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.3874499499797821},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33607202768325806},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.32685112953186035},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.30872976779937744},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.27385422587394714},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.08243998885154724},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.08154746890068054},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/info9070177","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info9070177","pdf_url":"https://www.mdpi.com/2078-2489/9/7/177/pdf?version=1532069693","source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Information","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:9a77fd233d3945fabff738ec2707e7c3","is_oa":false,"landing_page_url":"https://doaj.org/article/9a77fd233d3945fabff738ec2707e7c3","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Information, Vol 9, Iss 7, p 177 (2018)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2078-2489/9/7/177/","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3390/info9070177","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"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":"Information","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/info9070177","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info9070177","pdf_url":"https://www.mdpi.com/2078-2489/9/7/177/pdf?version=1532069693","source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Information","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Clean water and sanitation","score":0.8100000023841858,"id":"https://metadata.un.org/sdg/6"}],"awards":[{"id":"https://openalex.org/G8095425598","display_name":null,"funder_award_id":"No. 51709228","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8685861336","display_name":null,"funder_award_id":"51709228","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2883615841.pdf","grobid_xml":"https://content.openalex.org/works/W2883615841.grobid-xml"},"referenced_works_count":35,"referenced_works":["https://openalex.org/W1969655900","https://openalex.org/W1982074916","https://openalex.org/W2000982976","https://openalex.org/W2037072271","https://openalex.org/W2084678032","https://openalex.org/W2111072639","https://openalex.org/W2120390927","https://openalex.org/W2189160292","https://openalex.org/W2250153062","https://openalex.org/W2320636418","https://openalex.org/W2347276598","https://openalex.org/W2349029087","https://openalex.org/W2350166397","https://openalex.org/W2363472178","https://openalex.org/W2371648359","https://openalex.org/W2375160933","https://openalex.org/W2378228455","https://openalex.org/W2378302601","https://openalex.org/W2381143436","https://openalex.org/W2392666678","https://openalex.org/W2507165431","https://openalex.org/W2586354609","https://openalex.org/W2593374428","https://openalex.org/W2759519751","https://openalex.org/W2766420114","https://openalex.org/W2766769613","https://openalex.org/W2767272949","https://openalex.org/W2781875619","https://openalex.org/W2796339307","https://openalex.org/W2836722102","https://openalex.org/W3115577951","https://openalex.org/W3142622108","https://openalex.org/W6989261009","https://openalex.org/W7061212018","https://openalex.org/W7062036825"],"related_works":["https://openalex.org/W4391585328","https://openalex.org/W4318676890","https://openalex.org/W2039947585","https://openalex.org/W4385195237","https://openalex.org/W3178576217","https://openalex.org/W4285102093","https://openalex.org/W4210644201","https://openalex.org/W3111532652","https://openalex.org/W4381189085","https://openalex.org/W2510451507"],"abstract_inverted_index":{"The":[0,64,180],"matter":[1],"of":[2,8,125,147],"success":[3],"in":[4,27,54,68],"forecasting":[5,28,58],"precipitation":[6,29,57,66,95,202],"is":[7,48,116],"great":[9],"significance":[10],"to":[11,50,85,130,142,198],"flood":[12],"control":[13],"and":[14,17,21,59,76,162,174,194],"drought":[15],"relief,":[16],"water":[18],"resources":[19],"planning":[20],"management.":[22],"For":[23],"the":[24,52,61,69,92,122,132,144,148,186,200],"nonlinear":[25],"problem":[26],"time":[30,96,203],"series,":[31],"a":[32],"hybrid":[33,89,150,188],"prediction":[34,62,114,134,145,192],"model":[35,115,189],"based":[36],"on":[37],"variational":[38],"mode":[39,105],"decomposition":[40],"(VMD)":[41],"coupled":[42],"with":[43],"extreme":[44],"learning":[45],"machine":[46],"(ELM)":[47],"proposed":[49,149,187],"reduce":[51],"difficulty":[53],"modeling":[55],"monthly":[56,65,94,201],"improve":[60],"accuracy.":[63],"data":[67],"past":[70],"60":[71],"years":[72],"from":[73],"Yan\u2019an":[74],"City":[75],"Huashan":[77],"Mountain,":[78],"Shaanxi":[79],"Province,":[80],"are":[81,98,128,140],"used":[82,197],"as":[83],"cases":[84],"test":[86],"this":[87],"new":[88],"model.":[90],"First,":[91],"nonstationary":[93],"series":[97],"decomposed":[99],"into":[100],"several":[101],"relatively":[102],"stable":[103],"intrinsic":[104],"functions":[106],"(IMFs)":[107],"by":[108],"using":[109],"VMD.":[110],"Then,":[111],"an":[112],"ELM":[113],"established":[117],"for":[118],"each":[119],"IMF.":[120],"Next,":[121],"predicted":[123],"values":[124],"these":[126],"components":[127],"accumulated":[129],"obtain":[131],"final":[133],"results.":[135],"Finally,":[136],"three":[137],"predictive":[138],"indicators":[139],"adopted":[141],"measure":[143],"accuracy":[146,193],"model,":[151],"back":[152],"propagation":[153],"(BP)":[154],"neural":[155,158],"network,":[156],"Elman":[157],"network":[159],"(Elman),":[160],"ELM,":[161],"EMD-ELM":[163],"models:":[164],"mean":[165,170,175],"absolute":[166,176],"error":[167,172,178],"(MAE),":[168],"root":[169],"squared":[171],"(RMSE),":[173],"percentage":[177],"(MAPE).":[179],"experimental":[181],"simulation":[182],"results":[183],"show":[184],"that":[185],"has":[190],"higher":[191],"can":[195],"be":[196],"predict":[199],"series.":[204]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":1}],"updated_date":"2026-06-10T14:10:52.464848","created_date":"2025-10-10T00:00:00"}
