{"id":"https://openalex.org/W4387251710","doi":"https://doi.org/10.1109/ccis59572.2023.10263007","title":"Study on Soil Moisture Prediction based on the VMD-PCA-Informer Model","display_name":"Study on Soil Moisture Prediction based on the VMD-PCA-Informer Model","publication_year":2023,"publication_date":"2023-08-12","ids":{"openalex":"https://openalex.org/W4387251710","doi":"https://doi.org/10.1109/ccis59572.2023.10263007"},"language":"en","primary_location":{"id":"doi:10.1109/ccis59572.2023.10263007","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccis59572.2023.10263007","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 9th International Conference on Cloud Computing and Intelligent Systems (CCIS)","raw_type":"proceedings-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/A5112885597","display_name":"Ziliang Jia","orcid":null},"institutions":[{"id":"https://openalex.org/I78675632","display_name":"Beijing Information Science & Technology University","ror":"https://ror.org/04xnqep60","country_code":"CN","type":"education","lineage":["https://openalex.org/I78675632"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ziliang Jia","raw_affiliation_strings":["Beijing Information Science And Technology University,Beijing,China,100192"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Information Science And Technology University,Beijing,China,100192","institution_ids":["https://openalex.org/I78675632"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100620731","display_name":"Yonghong Liu","orcid":"https://orcid.org/0000-0002-7089-7541"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yonghong Liu","raw_affiliation_strings":["CMA Earth System Modeling and Prediction Centre,Beijing,China,100081"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CMA Earth System Modeling and Prediction Centre,Beijing,China,100081","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032383163","display_name":"Yiqun Wang","orcid":"https://orcid.org/0000-0001-7690-9788"},"institutions":[{"id":"https://openalex.org/I78675632","display_name":"Beijing Information Science & Technology University","ror":"https://ror.org/04xnqep60","country_code":"CN","type":"education","lineage":["https://openalex.org/I78675632"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yiqun Wang","raw_affiliation_strings":["Beijing Information Science And Technology University,Beijing,China,100192"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Information Science And Technology University,Beijing,China,100192","institution_ids":["https://openalex.org/I78675632"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045361189","display_name":"Wenbai Chen","orcid":"https://orcid.org/0000-0001-7683-2776"},"institutions":[{"id":"https://openalex.org/I78675632","display_name":"Beijing Information Science & Technology University","ror":"https://ror.org/04xnqep60","country_code":"CN","type":"education","lineage":["https://openalex.org/I78675632"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenbai Chen","raw_affiliation_strings":["Beijing Information Science And Technology University,Beijing,China,100192"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Information Science And Technology University,Beijing,China,100192","institution_ids":["https://openalex.org/I78675632"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2272,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.50809035,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"547","last_page":"551"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11312","display_name":"Soil Moisture and Remote Sensing","score":0.9986000061035156,"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/T11312","display_name":"Soil Moisture and Remote Sensing","score":0.9986000061035156,"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/T11404","display_name":"Irrigation Practices and Water Management","score":0.9901000261306763,"subfield":{"id":"https://openalex.org/subfields/1111","display_name":"Soil 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/T10266","display_name":"Plant Water Relations and Carbon Dynamics","score":0.98580002784729,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/water-content","display_name":"Water content","score":0.7210368514060974},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.715832531452179},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.637656569480896},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.5653395056724548},{"id":"https://openalex.org/keywords/moisture","display_name":"Moisture","score":0.46798086166381836},{"id":"https://openalex.org/keywords/soil-science","display_name":"Soil science","score":0.4607383608818054},{"id":"https://openalex.org/keywords/wind-speed","display_name":"Wind speed","score":0.4566267430782318},{"id":"https://openalex.org/keywords/humidity","display_name":"Humidity","score":0.4399717450141907},{"id":"https://openalex.org/keywords/pedotransfer-function","display_name":"Pedotransfer function","score":0.42960065603256226},{"id":"https://openalex.org/keywords/precipitation","display_name":"Precipitation","score":0.4273325204849243},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.34814804792404175},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.3403016924858093},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.30553221702575684},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.21255365014076233},{"id":"https://openalex.org/keywords/soil-water","display_name":"Soil water","score":0.20009735226631165},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.15903466939926147},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.15458989143371582},{"id":"https://openalex.org/keywords/geotechnical-engineering","display_name":"Geotechnical engineering","score":0.0797739326953888},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.07452142238616943}],"concepts":[{"id":"https://openalex.org/C24939127","wikidata":"https://www.wikidata.org/wiki/Q373499","display_name":"Water content","level":2,"score":0.7210368514060974},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.715832531452179},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.637656569480896},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.5653395056724548},{"id":"https://openalex.org/C176864760","wikidata":"https://www.wikidata.org/wiki/Q217651","display_name":"Moisture","level":2,"score":0.46798086166381836},{"id":"https://openalex.org/C159390177","wikidata":"https://www.wikidata.org/wiki/Q9161265","display_name":"Soil science","level":1,"score":0.4607383608818054},{"id":"https://openalex.org/C161067210","wikidata":"https://www.wikidata.org/wiki/Q1464943","display_name":"Wind speed","level":2,"score":0.4566267430782318},{"id":"https://openalex.org/C151420433","wikidata":"https://www.wikidata.org/wiki/Q180600","display_name":"Humidity","level":2,"score":0.4399717450141907},{"id":"https://openalex.org/C164285268","wikidata":"https://www.wikidata.org/wiki/Q7159349","display_name":"Pedotransfer function","level":4,"score":0.42960065603256226},{"id":"https://openalex.org/C107054158","wikidata":"https://www.wikidata.org/wiki/Q25257","display_name":"Precipitation","level":2,"score":0.4273325204849243},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.34814804792404175},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3403016924858093},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.30553221702575684},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.21255365014076233},{"id":"https://openalex.org/C159750122","wikidata":"https://www.wikidata.org/wiki/Q96621023","display_name":"Soil water","level":2,"score":0.20009735226631165},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.15903466939926147},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.15458989143371582},{"id":"https://openalex.org/C187320778","wikidata":"https://www.wikidata.org/wiki/Q1349130","display_name":"Geotechnical engineering","level":1,"score":0.0797739326953888},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.07452142238616943},{"id":"https://openalex.org/C63184880","wikidata":"https://www.wikidata.org/wiki/Q2783041","display_name":"Hydraulic conductivity","level":3,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ccis59572.2023.10263007","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccis59572.2023.10263007","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 9th International Conference on Cloud Computing and Intelligent Systems (CCIS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Clean water and sanitation","score":0.6200000047683716,"id":"https://metadata.un.org/sdg/6"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W2000982976","https://openalex.org/W2167461326","https://openalex.org/W2771019879","https://openalex.org/W2786455789","https://openalex.org/W2788586250","https://openalex.org/W2792209502","https://openalex.org/W2922882700","https://openalex.org/W2927513003","https://openalex.org/W2953222912","https://openalex.org/W2985376942","https://openalex.org/W3111808594","https://openalex.org/W3158254415","https://openalex.org/W3177318507","https://openalex.org/W3188803244","https://openalex.org/W4285816382","https://openalex.org/W4319923631","https://openalex.org/W4365453948","https://openalex.org/W4385245566","https://openalex.org/W6739901393"],"related_works":["https://openalex.org/W2579148721","https://openalex.org/W4387893611","https://openalex.org/W2347335694","https://openalex.org/W2091056927","https://openalex.org/W2067407580","https://openalex.org/W4317486777","https://openalex.org/W4389669152","https://openalex.org/W2038514069","https://openalex.org/W1967233468","https://openalex.org/W2009181529"],"abstract_inverted_index":{"Accurate":[0],"soil":[1,48,60,97,117,122,134],"moisture":[2,61,98,123,135],"prediction":[3,62,162,200],"is":[4,77,81,100,175,180,185],"crucial":[5],"for":[6,92,133],"the":[7,74,96,107,113,120,130,139,144,168,172,177,183,188,195,203],"effective":[8],"management":[9,16],"of":[10,116,143,154,171],"agricultural":[11,15],"water":[12],"resources,":[13],"ensuring":[14],"and":[17,21,30,40,73,119,141,182],"decision-making,":[18],"crop":[19],"monitoring":[20],"early":[22],"warning,":[23],"as":[24,26,34,127,157,159],"well":[25,158],"securing":[27],"food":[28],"supply":[29],"safety.":[31],"Factors":[32],"such":[33],"precipitation,":[35],"evaporation,":[36],"temperature,":[37],"humidity,":[38],"pressure,":[39],"wind":[41,90],"speed":[42,91],"have":[43],"a":[44,59,147],"significant":[45],"impact":[46],"on":[47],"moisture,":[49,118],"making":[50],"it":[51],"difficult":[52],"to":[53,83,129],"predict":[54],"accurately.":[55],"In":[56],"this":[57],"study,":[58],"method":[63],"combining":[64],"Principal":[65],"Component":[66],"Analysis":[67],"(PCA),":[68],"Variational":[69],"Mode":[70],"Decomposition":[71],"(VMD),":[72],"Informer":[75,131],"model":[76,174,197],"proposed.":[78],"Firstly,":[79],"PCA":[80],"applied":[82],"multidimensional":[84],"remote":[85],"sensing":[86],"data":[87,99,110,124,165],"that":[88,167,194],"influence":[89],"dimensionality":[93],"reduction.":[94],"Then,":[95],"decomposed":[101,114],"into":[102],"modes":[103,115],"using":[104],"VMD.":[105],"Finally,":[106],"reduced":[108],"feature":[109],"from":[111],"PCA,":[112],"original":[121],"are":[125],"merged":[126],"inputs":[128],"network":[132],"prediction.":[136],"To":[137],"showcase":[138],"benefits":[140],"practicality":[142],"proposed":[145],"approach,":[146],"comparison":[148],"was":[149],"conducted":[150],"against":[151],"other":[152,204],"methods":[153],"mode":[155],"decomposition":[156],"time":[160],"series":[161],"models.":[163,205],"Experimental":[164],"show":[166,193],"average":[169,178],"MAE":[170],"VMD-PCA-Informer":[173],"0.275,":[176],"RMSE":[179],"0.448,":[181],"R2_score":[184],"0.865":[186],"at":[187],"study":[189],"sites.":[190],"These":[191],"results":[192],"VMDPCA-Informer":[196],"has":[198],"better":[199],"accuracy":[201],"than":[202]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}