{"id":"https://openalex.org/W2030627222","doi":"https://doi.org/10.1109/icnc.2010.5584337","title":"LS-SVM forecast model of precipitation and runoff based on EMD","display_name":"LS-SVM forecast model of precipitation and runoff based on EMD","publication_year":2010,"publication_date":"2010-08-01","ids":{"openalex":"https://openalex.org/W2030627222","doi":"https://doi.org/10.1109/icnc.2010.5584337","mag":"2030627222"},"language":"en","primary_location":{"id":"doi:10.1109/icnc.2010.5584337","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icnc.2010.5584337","pdf_url":null,"source":{"id":"https://openalex.org/S4363608012","display_name":"2010 Sixth International Conference on Natural Computation","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 Sixth International Conference on Natural Computation","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/A5075738664","display_name":"Zhihong Ding","orcid":null},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]},{"id":"https://openalex.org/I4210158179","display_name":"Yellow River Institute of Hydraulic Research","ror":"https://ror.org/0506q7a98","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210155611","https://openalex.org/I4210158179"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhihong Ding","raw_affiliation_strings":["Tianjin University, TJU, Tianjin, China","Yellow River Institute of Hydraulic Research, Zhengzhou, China"],"affiliations":[{"raw_affiliation_string":"Tianjin University, TJU, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]},{"raw_affiliation_string":"Yellow River Institute of Hydraulic Research, Zhengzhou, China","institution_ids":["https://openalex.org/I4210158179"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100326961","display_name":"Jianwei Zhang","orcid":"https://orcid.org/0000-0002-2898-8108"},"institutions":[{"id":"https://openalex.org/I198645480","display_name":"North China University of Water Resources and Electric Power","ror":"https://ror.org/03acrzv41","country_code":"CN","type":"education","lineage":["https://openalex.org/I198645480"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianwei Zhang","raw_affiliation_strings":["North China University of Water Conservancy and Electric Power, Zhengzhou, China"],"affiliations":[{"raw_affiliation_string":"North China University of Water Conservancy and Electric Power, Zhengzhou, China","institution_ids":["https://openalex.org/I198645480"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012049340","display_name":"Guoquan Xie","orcid":null},"institutions":[{"id":"https://openalex.org/I4210127469","display_name":"Yalong Hydro (China)","ror":"https://ror.org/03f8xts90","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210127469"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guoquan Xie","raw_affiliation_strings":["Ertan Hydropower Development Company Limited, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"Ertan Hydropower Development Company Limited, Chengdu, China","institution_ids":["https://openalex.org/I4210127469"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5075738664"],"corresponding_institution_ids":["https://openalex.org/I162868743","https://openalex.org/I4210158179"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.20613342,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"19","issue":null,"first_page":"1721","last_page":"1725"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13734","display_name":"Advanced Computational Techniques and Applications","score":0.9904000163078308,"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/T13734","display_name":"Advanced Computational Techniques and Applications","score":0.9904000163078308,"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/T14157","display_name":"Environmental and Agricultural Sciences","score":0.9811000227928162,"subfield":{"id":"https://openalex.org/subfields/2312","display_name":"Water Science and Technology"},"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/T13717","display_name":"Advanced Algorithms and Applications","score":0.9796000123023987,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/precipitation","display_name":"Precipitation","score":0.6985267400741577},{"id":"https://openalex.org/keywords/hilbert\u2013huang-transform","display_name":"Hilbert\u2013Huang transform","score":0.6984632015228271},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.688019871711731},{"id":"https://openalex.org/keywords/surface-runoff","display_name":"Surface runoff","score":0.5783832669258118},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.570243239402771},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.530815601348877},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.523627519607544},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.514728307723999},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.4839104115962982},{"id":"https://openalex.org/keywords/quantitative-precipitation-forecast","display_name":"Quantitative precipitation forecast","score":0.45761221647262573},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.44664934277534485},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.33009952306747437},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32799339294433594},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2859616279602051},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2839871048927307},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.26958638429641724},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.26175808906555176},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2596505284309387},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.07885771989822388},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.06545275449752808}],"concepts":[{"id":"https://openalex.org/C107054158","wikidata":"https://www.wikidata.org/wiki/Q25257","display_name":"Precipitation","level":2,"score":0.6985267400741577},{"id":"https://openalex.org/C25570617","wikidata":"https://www.wikidata.org/wiki/Q1006462","display_name":"Hilbert\u2013Huang transform","level":3,"score":0.6984632015228271},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.688019871711731},{"id":"https://openalex.org/C50477045","wikidata":"https://www.wikidata.org/wiki/Q1444790","display_name":"Surface runoff","level":2,"score":0.5783832669258118},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.570243239402771},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.530815601348877},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.523627519607544},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.514728307723999},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.4839104115962982},{"id":"https://openalex.org/C140178040","wikidata":"https://www.wikidata.org/wiki/Q18402512","display_name":"Quantitative precipitation forecast","level":3,"score":0.45761221647262573},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.44664934277534485},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.33009952306747437},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32799339294433594},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2859616279602051},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2839871048927307},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.26958638429641724},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.26175808906555176},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2596505284309387},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.07885771989822388},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.06545275449752808},{"id":"https://openalex.org/C112633086","wikidata":"https://www.wikidata.org/wiki/Q381287","display_name":"White noise","level":2,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icnc.2010.5584337","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icnc.2010.5584337","pdf_url":null,"source":{"id":"https://openalex.org/S4363608012","display_name":"2010 Sixth International Conference on Natural Computation","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 Sixth International Conference on Natural Computation","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8299999833106995,"display_name":"Clean water and sanitation","id":"https://metadata.un.org/sdg/6"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W1988007167","https://openalex.org/W2007221293","https://openalex.org/W2103504566","https://openalex.org/W2106665847","https://openalex.org/W2158994553","https://openalex.org/W2360600211","https://openalex.org/W2365726656","https://openalex.org/W2367961108","https://openalex.org/W6983775247","https://openalex.org/W7043430944"],"related_works":["https://openalex.org/W3014107421","https://openalex.org/W2363056446","https://openalex.org/W2081563414","https://openalex.org/W2359718298","https://openalex.org/W2377062149","https://openalex.org/W2380939102","https://openalex.org/W154554909","https://openalex.org/W2072581623","https://openalex.org/W2011248322","https://openalex.org/W1915398038"],"abstract_inverted_index":{"Through":[0],"analyzing":[1],"problem":[2],"of":[3,14,20,54],"Wavelet":[4],"Transform,":[5],"the":[6,15,37,67],"annual":[7],"precipitation":[8,38,55],"series":[9,29,39,98],"from":[10],"1956":[11],"to":[12,94,113,123],"2000":[13],"two":[16],"sub-water":[17],"resources":[18],"regions":[19],"upper":[21],"Lanzhou":[22],"are":[23],"decomposed":[24],"into":[25,99],"multiple":[26,101,121],"time":[27,97,102],"scale":[28,103],"with":[30,66,117],"EMD":[31,60],"method.":[32],"The":[33],"results":[34],"show":[35],"that":[36,42],"have":[40],"periods":[41],"about":[43],"3,":[44],"4~8,":[45],"11":[46],"and":[47,56,63,79,111,120],"22":[48],"years.":[49],"A":[50],"LS-SVM":[51],"forecast":[52,71],"model":[53,125],"runoff":[57],"based":[58],"on":[59],"is":[61],"established":[62],"then":[64,112],"compared":[65],"corresponding":[68],"multivariable":[69],"regression":[70],"model.":[72],"It":[73],"shows":[74],"that,":[75],"as":[76,91],"a":[77,92],"new":[78],"original":[80],"signal":[81],"processing":[82],"method,":[83],"Empirical":[84],"Mode":[85],"Decomposition,":[86],"EMD,":[87],"can":[88],"be":[89],"used":[90],"tool":[93],"decompose":[95],"hydrological":[96],"exact":[100],"sub-series":[104],"for":[105],"finding":[106],"their":[107],"local":[108],"change":[109],"rule,":[110],"supply":[114],"input":[115],"variables":[116],"high":[118],"quality":[119,126],"levels":[122],"enhance":[124],"remarkably.":[127]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}