{"id":"https://openalex.org/W3113967544","doi":"https://doi.org/10.1109/ictc49870.2020.9289534","title":"Enhancing Prediction of Chlorophyll-a Concentration with Feature Extraction using Higher-Order Partial Least Squares","display_name":"Enhancing Prediction of Chlorophyll-a Concentration with Feature Extraction using Higher-Order Partial Least Squares","publication_year":2020,"publication_date":"2020-10-21","ids":{"openalex":"https://openalex.org/W3113967544","doi":"https://doi.org/10.1109/ictc49870.2020.9289534","mag":"3113967544"},"language":"en","primary_location":{"id":"doi:10.1109/ictc49870.2020.9289534","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ictc49870.2020.9289534","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Conference on Information and Communication Technology Convergence (ICTC)","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/A5000217257","display_name":"Taewhi Lee","orcid":"https://orcid.org/0000-0002-9846-1862"},"institutions":[{"id":"https://openalex.org/I142401562","display_name":"Electronics and Telecommunications Research Institute","ror":"https://ror.org/03ysstz10","country_code":"KR","type":"facility","lineage":["https://openalex.org/I142401562","https://openalex.org/I2801339556","https://openalex.org/I4210144908","https://openalex.org/I4387152098"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Taewhi Lee","raw_affiliation_strings":["Smart Data Research Section, AI Research Lab., ETRI (Electronics and Telecommunications Research Institute), Daejeon, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Smart Data Research Section, AI Research Lab., ETRI (Electronics and Telecommunications Research Institute), Daejeon, Republic of Korea","institution_ids":["https://openalex.org/I142401562"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100952349","display_name":"Jang\u2010Ho Choi","orcid":"https://orcid.org/0000-0002-9280-051X"},"institutions":[{"id":"https://openalex.org/I142401562","display_name":"Electronics and Telecommunications Research Institute","ror":"https://ror.org/03ysstz10","country_code":"KR","type":"facility","lineage":["https://openalex.org/I142401562","https://openalex.org/I2801339556","https://openalex.org/I4210144908","https://openalex.org/I4387152098"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jang-Ho Choi","raw_affiliation_strings":["Smart Data Research Section, AI Research Lab., ETRI (Electronics and Telecommunications Research Institute), Daejeon, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Smart Data Research Section, AI Research Lab., ETRI (Electronics and Telecommunications Research Institute), Daejeon, Republic of Korea","institution_ids":["https://openalex.org/I142401562"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055694325","display_name":"Miyoung Jang","orcid":"https://orcid.org/0000-0003-0723-5788"},"institutions":[{"id":"https://openalex.org/I142401562","display_name":"Electronics and Telecommunications Research Institute","ror":"https://ror.org/03ysstz10","country_code":"KR","type":"facility","lineage":["https://openalex.org/I142401562","https://openalex.org/I2801339556","https://openalex.org/I4210144908","https://openalex.org/I4387152098"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Miyoung Jang","raw_affiliation_strings":["Smart Data Research Section, AI Research Lab., ETRI (Electronics and Telecommunications Research Institute), Daejeon, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Smart Data Research Section, AI Research Lab., ETRI (Electronics and Telecommunications Research Institute), Daejeon, Republic of Korea","institution_ids":["https://openalex.org/I142401562"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009873258","display_name":"Jongho Won","orcid":"https://orcid.org/0000-0002-3962-6962"},"institutions":[{"id":"https://openalex.org/I142401562","display_name":"Electronics and Telecommunications Research Institute","ror":"https://ror.org/03ysstz10","country_code":"KR","type":"facility","lineage":["https://openalex.org/I142401562","https://openalex.org/I2801339556","https://openalex.org/I4210144908","https://openalex.org/I4387152098"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jongho Won","raw_affiliation_strings":["Smart Data Research Section, AI Research Lab., ETRI (Electronics and Telecommunications Research Institute), Daejeon, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Smart Data Research Section, AI Research Lab., ETRI (Electronics and Telecommunications Research Institute), Daejeon, Republic of Korea","institution_ids":["https://openalex.org/I142401562"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032837167","display_name":"Jiyong Kim","orcid":"https://orcid.org/0000-0002-9999-736X"},"institutions":[{"id":"https://openalex.org/I142401562","display_name":"Electronics and Telecommunications Research Institute","ror":"https://ror.org/03ysstz10","country_code":"KR","type":"facility","lineage":["https://openalex.org/I142401562","https://openalex.org/I2801339556","https://openalex.org/I4210144908","https://openalex.org/I4387152098"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jiyong Kim","raw_affiliation_strings":["Smart Data Research Section, AI Research Lab., ETRI (Electronics and Telecommunications Research Institute), Daejeon, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Smart Data Research Section, AI Research Lab., ETRI (Electronics and Telecommunications Research Institute), Daejeon, Republic of Korea","institution_ids":["https://openalex.org/I142401562"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5000217257"],"corresponding_institution_ids":["https://openalex.org/I142401562"],"apc_list":null,"apc_paid":null,"fwci":0.6652,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.72188021,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1666","last_page":"1668"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14249","display_name":"Water Quality Monitoring and Analysis","score":0.9958000183105469,"subfield":{"id":"https://openalex.org/subfields/2311","display_name":"Industrial and Manufacturing 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/T14249","display_name":"Water Quality Monitoring and Analysis","score":0.9958000183105469,"subfield":{"id":"https://openalex.org/subfields/2311","display_name":"Industrial and Manufacturing 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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9872000217437744,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12697","display_name":"Water Quality Monitoring Technologies","score":0.9739000201225281,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/partial-least-squares-regression","display_name":"Partial least squares regression","score":0.7997251749038696},{"id":"https://openalex.org/keywords/algal-bloom","display_name":"Algal bloom","score":0.6739033460617065},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6457877159118652},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6081528067588806},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5101761817932129},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4632279872894287},{"id":"https://openalex.org/keywords/chlorophyll-a","display_name":"Chlorophyll a","score":0.4577959179878235},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.42096754908561707},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3820072412490845},{"id":"https://openalex.org/keywords/ecology","display_name":"Ecology","score":0.12786048650741577},{"id":"https://openalex.org/keywords/botany","display_name":"Botany","score":0.06154352426528931},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.0593145489692688}],"concepts":[{"id":"https://openalex.org/C22354355","wikidata":"https://www.wikidata.org/wiki/Q422009","display_name":"Partial least squares regression","level":2,"score":0.7997251749038696},{"id":"https://openalex.org/C120305227","wikidata":"https://www.wikidata.org/wiki/Q326139","display_name":"Algal bloom","level":4,"score":0.6739033460617065},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6457877159118652},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6081528067588806},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5101761817932129},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4632279872894287},{"id":"https://openalex.org/C2778902199","wikidata":"https://www.wikidata.org/wiki/Q133878","display_name":"Chlorophyll a","level":2,"score":0.4577959179878235},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42096754908561707},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3820072412490845},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.12786048650741577},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.06154352426528931},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0593145489692688},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C142796444","wikidata":"https://www.wikidata.org/wiki/Q181394","display_name":"Nutrient","level":2,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C2780892065","wikidata":"https://www.wikidata.org/wiki/Q184755","display_name":"Phytoplankton","level":3,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ictc49870.2020.9289534","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ictc49870.2020.9289534","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Conference on Information and Communication Technology Convergence (ICTC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W90912833","https://openalex.org/W1485009520","https://openalex.org/W1967696752","https://openalex.org/W2032044732","https://openalex.org/W2148143831","https://openalex.org/W2215056949","https://openalex.org/W2289019118","https://openalex.org/W2766520584","https://openalex.org/W2782506500","https://openalex.org/W2886117254","https://openalex.org/W2915117297","https://openalex.org/W2943411962","https://openalex.org/W2967229946","https://openalex.org/W3036590418","https://openalex.org/W6603766316","https://openalex.org/W6628877408","https://openalex.org/W6629544949"],"related_works":["https://openalex.org/W1989457222","https://openalex.org/W2158863190","https://openalex.org/W2770989956","https://openalex.org/W2359803370","https://openalex.org/W4386765169","https://openalex.org/W2380916892","https://openalex.org/W2229792849","https://openalex.org/W2356011625","https://openalex.org/W2039072424","https://openalex.org/W2392260757"],"abstract_inverted_index":{"Harmful":[0],"algal":[1,28],"blooms":[2],"can":[3,79],"cause":[4],"significant":[5],"negative":[6],"impacts":[7],"on":[8],"the":[9,25,46,57,74,82],"health":[10],"of":[11,27],"humans":[12],"and":[13],"other":[14],"organisms.":[15],"It":[16],"is":[17],"useful":[18],"to":[19,55],"predict":[20],"chlorophyll-a":[21],"concentration":[22],"accurately":[23],"for":[24,38],"forecast":[26],"blooms.":[29],"While":[30],"convolutional":[31],"machine":[32],"learning":[33],"models":[34],"are":[35],"often":[36],"used":[37],"such":[39],"prediction,":[40],"they":[41],"may":[42],"not":[43],"fully":[44],"consider":[45],"relationships":[47],"among":[48],"input":[49],"features.":[50],"We":[51],"propose":[52],"an":[53],"approach":[54],"enhance":[56],"prediction":[58,83],"by":[59],"extracting":[60],"latent":[61],"features":[62],"using":[63,77],"higher-order":[64],"partial":[65],"least":[66],"squares":[67],"(HOPLS).":[68],"The":[69],"experimental":[70],"results":[71],"show":[72],"that":[73],"feature":[75],"extraction":[76],"HOPLS":[78],"significantly":[80],"improve":[81],"accuracy,":[84],"especially":[85],"in":[86],"critical":[87],"cases.":[88]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
