{"id":"https://openalex.org/W2112081742","doi":"https://doi.org/10.1109/fuzz.2003.1206622","title":"Modelling of river discharges using neural networks derived from support vector regression","display_name":"Modelling of river discharges using neural networks derived from support vector regression","publication_year":2004,"publication_date":"2004-03-22","ids":{"openalex":"https://openalex.org/W2112081742","doi":"https://doi.org/10.1109/fuzz.2003.1206622","mag":"2112081742"},"language":"en","primary_location":{"id":"doi:10.1109/fuzz.2003.1206622","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fuzz.2003.1206622","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 12th IEEE International Conference on Fuzzy Systems, 2003. FUZZ '03.","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/A5091903600","display_name":"Kwok-Hung Choy","orcid":null},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":true,"raw_author_name":"K.Y. Choy","raw_affiliation_strings":["Department of Mechanical Engineering, University of Hong Kong, China","[Dept. of Mech. Eng., Hong Kong Univ., China]"],"affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, University of Hong Kong, China","institution_ids":["https://openalex.org/I889458895"]},{"raw_affiliation_string":"[Dept. of Mech. Eng., Hong Kong Univ., China]","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101782697","display_name":"C.W. Chan","orcid":"https://orcid.org/0000-0002-8048-3166"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"C.W. Chan","raw_affiliation_strings":["Department of Mechanical Engineering, University of Hong Kong, China","[Dept. of Mech. Eng., Hong Kong Univ., China]"],"affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, University of Hong Kong, China","institution_ids":["https://openalex.org/I889458895"]},{"raw_affiliation_string":"[Dept. of Mech. Eng., Hong Kong Univ., China]","institution_ids":["https://openalex.org/I889458895"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5091903600"],"corresponding_institution_ids":["https://openalex.org/I889458895"],"apc_list":null,"apc_paid":null,"fwci":0.4497,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.75504544,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"2","issue":null,"first_page":"1321","last_page":"1326"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9994999766349792,"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/T10320","display_name":"Neural Networks and Applications","score":0.9994999766349792,"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/T11490","display_name":"Hydrological Forecasting Using AI","score":0.9977999925613403,"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/T11206","display_name":"Model Reduction and Neural Networks","score":0.9926000237464905,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.7510821223258972},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.6932764649391174},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6517813801765442},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6380844116210938},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.6339318156242371},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5185214281082153},{"id":"https://openalex.org/keywords/associative-property","display_name":"Associative property","score":0.4711301028728485},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4501500129699707},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4488619863986969},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3209553360939026},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.31777745485305786},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2210874855518341}],"concepts":[{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.7510821223258972},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.6932764649391174},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6517813801765442},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6380844116210938},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.6339318156242371},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5185214281082153},{"id":"https://openalex.org/C159423971","wikidata":"https://www.wikidata.org/wiki/Q177251","display_name":"Associative property","level":2,"score":0.4711301028728485},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4501500129699707},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4488619863986969},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3209553360939026},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.31777745485305786},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2210874855518341},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/fuzz.2003.1206622","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fuzz.2003.1206622","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 12th IEEE International Conference on Fuzzy Systems, 2003. FUZZ '03.","raw_type":"proceedings-article"},{"id":"pmh:oai:hub.hku.hk:10722/46674","is_oa":false,"landing_page_url":"http://hdl.handle.net/10722/46674","pdf_url":null,"source":{"id":"https://openalex.org/S4377196271","display_name":"The HKU Scholars Hub (University of Hong Kong)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I889458895","host_organization_name":"University of Hong Kong","host_organization_lineage":["https://openalex.org/I889458895"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference_Paper"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W369739517","https://openalex.org/W1488957217","https://openalex.org/W1492468531","https://openalex.org/W1669104078","https://openalex.org/W2055522016","https://openalex.org/W2103414828","https://openalex.org/W2119821739","https://openalex.org/W2137983211","https://openalex.org/W2141517479","https://openalex.org/W2149350706","https://openalex.org/W2156909104","https://openalex.org/W4239510810","https://openalex.org/W4388249735"],"related_works":["https://openalex.org/W2355927362","https://openalex.org/W2354062721","https://openalex.org/W2992977501","https://openalex.org/W2385384103","https://openalex.org/W2385643646","https://openalex.org/W4362499384","https://openalex.org/W2367868770","https://openalex.org/W2084236348","https://openalex.org/W2360601255","https://openalex.org/W3027004089"],"abstract_inverted_index":{"Neural":[0,118],"networks":[1],"are":[2,34,39,90,169],"often":[3,35],"used":[4],"to":[5,68,76,113],"model":[6],"complex":[7],"and":[8,20,43,101,146],"nonlinear":[9,15,141],"systems,":[10],"as":[11,114,131],"they":[12,38],"can":[13,21,48,53,159],"approximate":[14],"systems":[16],"with":[17,129],"arbitrary":[18],"accuracy":[19],"be":[22,49,55],"trained":[23],"from":[24,83,92,138,156],"data.":[25],"Amongst":[26],"the":[27,58,61,70,73,78,84,115,124,134,140,157],"neural":[28],"networks,":[29],"Associative":[30],"Memory":[31],"Networks":[32,119],"(AMNs)":[33],"used,":[36],"since":[37],"less":[40],"computation":[41],"intensive,":[42],"yet":[44],"good":[45],"generalization":[46],"results":[47],"obtained.":[50,150],"However,":[51],"this":[52,107,122],"only":[54],"achieved":[56],"if":[57],"structure":[59,71],"of":[60,72,109,126,153,163],"AMNs":[62,74,110],"is":[63,75,111,136,149],"suitably":[64],"chosen.":[65],"An":[66],"approach":[67],"choose":[69],"use":[77],"Support":[79,85,116],"Vectors":[80],"(SVs)":[81],"obtained":[82,91],"Vector":[86,117],"Machines.":[87],"The":[88,151],"SVs":[89],"a":[93,97],"constrained":[94],"optimization":[95],"for":[96],"given":[98],"data":[99],"set":[100],"an":[102],"error":[103],"bound.":[104],"For":[105],"convenience,":[106],"class":[108],"referred":[112],"(SVNNs).":[120],"In":[121],"paper,":[123],"modelling":[125],"river":[127,147,154,165],"discharges":[128,148,155,166],"rainfall":[130,145],"input":[132],"using":[133],"SVNN":[135,158],"presented,":[137],"which":[139],"dynamic":[142],"relationship":[143],"between":[144],"prediction":[152],"give":[160],"early":[161],"warning":[162],"severe":[164],"when":[167],"there":[168],"heavy":[170],"rainfalls.":[171]},"counts_by_year":[{"year":2012,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}