{"id":"https://openalex.org/W4394864323","doi":"https://doi.org/10.1145/3650215.3650398","title":"Analysis of Machine Learning Methods for Water Quality Evaluation of Penaeus Vannamei","display_name":"Analysis of Machine Learning Methods for Water Quality Evaluation of Penaeus Vannamei","publication_year":2023,"publication_date":"2023-10-27","ids":{"openalex":"https://openalex.org/W4394864323","doi":"https://doi.org/10.1145/3650215.3650398"},"language":"en","primary_location":{"id":"doi:10.1145/3650215.3650398","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3650215.3650398","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 4th International Conference on Machine Learning and Computer Application","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/A5066109759","display_name":"Peng Xiao-hong","orcid":"https://orcid.org/0009-0008-0721-573X"},"institutions":[{"id":"https://openalex.org/I79223203","display_name":"Guangdong Ocean University","ror":"https://ror.org/0462wa640","country_code":"CN","type":"education","lineage":["https://openalex.org/I79223203"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiaohong Peng","raw_affiliation_strings":["School of Mathematics and Computer Science, Guangdong Ocean University, China"],"raw_orcid":"https://orcid.org/0009-0008-0721-573X","affiliations":[{"raw_affiliation_string":"School of Mathematics and Computer Science, Guangdong Ocean University, China","institution_ids":["https://openalex.org/I79223203"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101524612","display_name":"Zixin Li","orcid":"https://orcid.org/0009-0005-3425-5727"},"institutions":[{"id":"https://openalex.org/I79223203","display_name":"Guangdong Ocean University","ror":"https://ror.org/0462wa640","country_code":"CN","type":"education","lineage":["https://openalex.org/I79223203"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zixin Li","raw_affiliation_strings":["School of Mathematics and Computer Science, Guangdong Ocean University, China"],"raw_orcid":"https://orcid.org/0009-0005-3425-5727","affiliations":[{"raw_affiliation_string":"School of Mathematics and Computer Science, Guangdong Ocean University, China","institution_ids":["https://openalex.org/I79223203"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102745978","display_name":"Zebin Ma","orcid":"https://orcid.org/0009-0008-3410-4111"},"institutions":[{"id":"https://openalex.org/I79223203","display_name":"Guangdong Ocean University","ror":"https://ror.org/0462wa640","country_code":"CN","type":"education","lineage":["https://openalex.org/I79223203"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zebin Ma","raw_affiliation_strings":["School of Mathematics and Computer Science, Guangdong Ocean University, China"],"raw_orcid":"https://orcid.org/0009-0008-3410-4111","affiliations":[{"raw_affiliation_string":"School of Mathematics and Computer Science, Guangdong Ocean University, China","institution_ids":["https://openalex.org/I79223203"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033125254","display_name":"Ying Zhang","orcid":"https://orcid.org/0009-0001-0669-7385"},"institutions":[{"id":"https://openalex.org/I79223203","display_name":"Guangdong Ocean University","ror":"https://ror.org/0462wa640","country_code":"CN","type":"education","lineage":["https://openalex.org/I79223203"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ying Zhang","raw_affiliation_strings":["School of Mathematics and Computer Science, Guangdong Ocean University, China"],"raw_orcid":"https://orcid.org/0009-0001-0669-7385","affiliations":[{"raw_affiliation_string":"School of Mathematics and Computer Science, Guangdong Ocean University, China","institution_ids":["https://openalex.org/I79223203"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5066109759"],"corresponding_institution_ids":["https://openalex.org/I79223203"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.25133943,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1032","last_page":"1041"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12319","display_name":"Fish Biology and Ecology Studies","score":0.989300012588501,"subfield":{"id":"https://openalex.org/subfields/1104","display_name":"Aquatic 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"}},"topics":[{"id":"https://openalex.org/T12319","display_name":"Fish Biology and Ecology Studies","score":0.989300012588501,"subfield":{"id":"https://openalex.org/subfields/1104","display_name":"Aquatic 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/T12697","display_name":"Water Quality Monitoring Technologies","score":0.9890999794006348,"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/T10450","display_name":"Aquaculture Nutrition and Growth","score":0.9782000184059143,"subfield":{"id":"https://openalex.org/subfields/1104","display_name":"Aquatic 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"}}],"keywords":[{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6923527717590332},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6587249636650085},{"id":"https://openalex.org/keywords/aquaculture","display_name":"Aquaculture","score":0.6047393083572388},{"id":"https://openalex.org/keywords/penaeus","display_name":"Penaeus","score":0.5829522609710693},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.5708685517311096},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.523894190788269},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5071797370910645},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.4715476334095001},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.4659598469734192},{"id":"https://openalex.org/keywords/water-quality","display_name":"Water quality","score":0.4618396461009979},{"id":"https://openalex.org/keywords/agriculture","display_name":"Agriculture","score":0.4187034070491791},{"id":"https://openalex.org/keywords/fishery","display_name":"Fishery","score":0.300260066986084},{"id":"https://openalex.org/keywords/ecology","display_name":"Ecology","score":0.1395079493522644},{"id":"https://openalex.org/keywords/shrimp","display_name":"Shrimp","score":0.12123236060142517},{"id":"https://openalex.org/keywords/fish-actinopterygii","display_name":"Fish <Actinopterygii>","score":0.09889411926269531},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.09102654457092285}],"concepts":[{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6923527717590332},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6587249636650085},{"id":"https://openalex.org/C86909935","wikidata":"https://www.wikidata.org/wiki/Q188989","display_name":"Aquaculture","level":3,"score":0.6047393083572388},{"id":"https://openalex.org/C2776599375","wikidata":"https://www.wikidata.org/wiki/Q3011709","display_name":"Penaeus","level":3,"score":0.5829522609710693},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.5708685517311096},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.523894190788269},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5071797370910645},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.4715476334095001},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4659598469734192},{"id":"https://openalex.org/C2780797713","wikidata":"https://www.wikidata.org/wiki/Q625376","display_name":"Water quality","level":2,"score":0.4618396461009979},{"id":"https://openalex.org/C118518473","wikidata":"https://www.wikidata.org/wiki/Q11451","display_name":"Agriculture","level":2,"score":0.4187034070491791},{"id":"https://openalex.org/C505870484","wikidata":"https://www.wikidata.org/wiki/Q180538","display_name":"Fishery","level":1,"score":0.300260066986084},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.1395079493522644},{"id":"https://openalex.org/C2776841996","wikidata":"https://www.wikidata.org/wiki/Q1517781","display_name":"Shrimp","level":2,"score":0.12123236060142517},{"id":"https://openalex.org/C2909208804","wikidata":"https://www.wikidata.org/wiki/Q127282","display_name":"Fish <Actinopterygii>","level":2,"score":0.09889411926269531},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.09102654457092285},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3650215.3650398","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3650215.3650398","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 4th International Conference on Machine Learning and Computer Application","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4399999976158142,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":6,"referenced_works":["https://openalex.org/W2909851444","https://openalex.org/W2993627023","https://openalex.org/W3163573151","https://openalex.org/W4280519114","https://openalex.org/W4283457594","https://openalex.org/W4362544675"],"related_works":["https://openalex.org/W4389954502","https://openalex.org/W2771255398","https://openalex.org/W2993277077","https://openalex.org/W2930428186","https://openalex.org/W3200027047","https://openalex.org/W4385770464","https://openalex.org/W3125536479","https://openalex.org/W3120363735","https://openalex.org/W4214820172","https://openalex.org/W2394323384"],"abstract_inverted_index":{"In":[0],"global":[1],"aquaculture,":[2],"Penaeus":[3,47,108],"vannamei":[4,109],"stands":[5],"out":[6],"due":[7],"to":[8,46,97],"its":[9,18,85],"immense":[10],"economic":[11],"importance.":[12],"Water":[13],"quality,":[14],"being":[15],"pivotal":[16],"for":[17,70,107,115,137],"successful":[19],"cultivation,":[20],"demands":[21],"precise":[22],"evaluation":[23,105],"techniques.":[24],"This":[25,90,127],"research":[26,128],"undertook":[27],"a":[28,37,99,112],"meticulous":[29],"systematic":[30],"review":[31],"and,":[32],"leveraging":[33],"data":[34],"mining,":[35],"crafted":[36],"rich":[38],"dataset":[39],"of":[40,141],"50,000":[41],"water":[42,103],"quality":[43,104],"samples":[44],"pertinent":[45],"vannamei.":[48],"Diving":[49],"deep":[50],"into":[51],"machine":[52,94],"learning,":[53],"we":[54],"assessed":[55],"four":[56],"key":[57],"algorithms:":[58],"decision":[59],"tree,":[60],"Bayesian,":[61],"k-nearest":[62],"neighbor,":[63],"and":[64,88,101,119,134],"support":[65],"vector":[66],"machine,":[67],"each":[68],"tailored":[69],"intricate":[71],"multi-feature":[72],"multi-classification":[73],"challenges.":[74],"Of":[75],"these,":[76],"the":[77,116,138,142],"Gaussian":[78],"Parsimonious":[79],"Bayes-based":[80],"model":[81,106],"was":[82],"distinguished":[83],"by":[84],"superior":[86],"accuracy":[87],"efficiency.":[89],"study":[91],"successfully":[92],"applied":[93],"learning":[95],"techniques":[96],"develop":[98],"reliable":[100],"efficient":[102],"farming,":[110],"offering":[111],"scientific":[113,132],"tool":[114],"aquaculture":[117,143],"industry":[118],"facilitating":[120],"more":[121],"efficient,":[122],"scientifically":[123],"informed":[124],"farming":[125],"management.":[126],"contributes":[129],"an":[130],"innovative":[131],"approach":[133],"theoretical":[135],"foundation":[136],"sustainable":[139],"growth":[140],"industry.":[144]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}