{"id":"https://openalex.org/W4389332647","doi":"https://doi.org/10.1109/cce60043.2023.10332877","title":"Decision Tree Learning Enhancement for Dynamic Data with Disturbances and Uncertainties via Integration of DWT and Nonlinear SVM","display_name":"Decision Tree Learning Enhancement for Dynamic Data with Disturbances and Uncertainties via Integration of DWT and Nonlinear SVM","publication_year":2023,"publication_date":"2023-10-25","ids":{"openalex":"https://openalex.org/W4389332647","doi":"https://doi.org/10.1109/cce60043.2023.10332877"},"language":"en","primary_location":{"id":"doi:10.1109/cce60043.2023.10332877","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/cce60043.2023.10332877","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 20th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE)","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/A5101519387","display_name":"Zhengmao Ye","orcid":"https://orcid.org/0000-0001-8897-574X"},"institutions":[{"id":"https://openalex.org/I145610796","display_name":"Southern University and Agricultural and Mechanical College","ror":"https://ror.org/04r3m2882","country_code":"US","type":"education","lineage":["https://openalex.org/I145610796"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Zhengmao Ye","raw_affiliation_strings":["Southern University,College of Science and Engineering,Baton Rouge,USA","College of Science and Engineering, Southern University, Baton Rouge, USA"],"affiliations":[{"raw_affiliation_string":"Southern University,College of Science and Engineering,Baton Rouge,USA","institution_ids":["https://openalex.org/I145610796"]},{"raw_affiliation_string":"College of Science and Engineering, Southern University, Baton Rouge, USA","institution_ids":["https://openalex.org/I145610796"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058304509","display_name":"Hang Yin","orcid":"https://orcid.org/0000-0002-4600-5881"},"institutions":[{"id":"https://openalex.org/I145610796","display_name":"Southern University and Agricultural and Mechanical College","ror":"https://ror.org/04r3m2882","country_code":"US","type":"education","lineage":["https://openalex.org/I145610796"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hang Yin","raw_affiliation_strings":["Southern University,College of Science and Engineering,Baton Rouge,USA","College of Science and Engineering, Southern University, Baton Rouge, USA"],"affiliations":[{"raw_affiliation_string":"Southern University,College of Science and Engineering,Baton Rouge,USA","institution_ids":["https://openalex.org/I145610796"]},{"raw_affiliation_string":"College of Science and Engineering, Southern University, Baton Rouge, USA","institution_ids":["https://openalex.org/I145610796"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101519387"],"corresponding_institution_ids":["https://openalex.org/I145610796"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.16948585,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9945999979972839,"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"}},"topics":[{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9945999979972839,"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/T10876","display_name":"Fault Detection and Control Systems","score":0.9811000227928162,"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"}},{"id":"https://openalex.org/T11324","display_name":"Spectroscopy Techniques in Biomedical and Chemical Research","score":0.9714000225067139,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.7698099613189697},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.655981719493866},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.6189342737197876},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6145195960998535},{"id":"https://openalex.org/keywords/discrete-wavelet-transform","display_name":"Discrete wavelet transform","score":0.6068561673164368},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.5220403671264648},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.517454206943512},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5160346031188965},{"id":"https://openalex.org/keywords/binary-tree","display_name":"Binary tree","score":0.4174732565879822},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4047636091709137},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.29818272590637207},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.2852621078491211},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.22730347514152527}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7698099613189697},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.655981719493866},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.6189342737197876},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6145195960998535},{"id":"https://openalex.org/C46286280","wikidata":"https://www.wikidata.org/wiki/Q2414958","display_name":"Discrete wavelet transform","level":4,"score":0.6068561673164368},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.5220403671264648},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.517454206943512},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5160346031188965},{"id":"https://openalex.org/C197855036","wikidata":"https://www.wikidata.org/wiki/Q380172","display_name":"Binary tree","level":2,"score":0.4174732565879822},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4047636091709137},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.29818272590637207},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.2852621078491211},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.22730347514152527},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cce60043.2023.10332877","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/cce60043.2023.10332877","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 20th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W1945924242","https://openalex.org/W2073514162","https://openalex.org/W2101706868","https://openalex.org/W2104528845","https://openalex.org/W2153038960","https://openalex.org/W2153534417","https://openalex.org/W3136741359","https://openalex.org/W4239399610","https://openalex.org/W4310007215"],"related_works":["https://openalex.org/W2090763504","https://openalex.org/W148178222","https://openalex.org/W2104657898","https://openalex.org/W1948992892","https://openalex.org/W1886884218","https://openalex.org/W2369081777","https://openalex.org/W4224922629","https://openalex.org/W2513092100","https://openalex.org/W2104406636","https://openalex.org/W2049449421"],"abstract_inverted_index":{"A":[0],"simple":[1],"technical":[2],"integration":[3],"approach":[4,87],"is":[5,20,54],"used":[6],"to":[7,22,27,39,91,107,122],"classify":[8],"dynamic":[9,129],"data":[10,25,58,96,125],"with":[11],"various":[12],"disturbances":[13,45],"and":[14,31,46,60,73,79,113],"uncertainties.":[15,47],"Discrete":[16],"Wavelet":[17],"Transform":[18],"(DWT)":[19],"introduced":[21],"decompose":[23],"nonlinear":[24,49,74],"subject":[26],"classification":[28,97],"into":[29],"approximation":[30],"detail":[32],"components":[33],"at":[34],"multiple":[35,82],"levels,":[36],"in":[37,81],"order":[38],"extract":[40],"the":[41],"intrinsic":[42],"information":[43],"against":[44],"The":[48],"Support":[50],"Vector":[51],"Machine":[52],"(SVM)":[53],"then":[55],"applied":[56,90,106],"for":[57,98],"training":[59],"binary":[61],"tree":[62],"decision":[63,114],"making":[64],"as":[65,67,128],"well":[66],"learning":[68,115],"enhancement.":[69,116],"Integration":[70],"of":[71,131],"DWT":[72],"SVM":[75],"has":[76,88,104],"demonstrated":[77],"feasibility":[78],"effectiveness":[80],"case":[83],"studies.":[84],"Firstly,":[85],"this":[86],"been":[89,105],"time":[92],"domain":[93,109,124],"transient":[94],"experimental":[95],"Rapid":[99],"Compression":[100],"Machine.":[101],"Secondly,":[102],"it":[103],"frequency":[108],"Raman":[110],"spectral":[111],"differentiation":[112],"It":[117],"can":[118],"also":[119],"be":[120],"extended":[121],"spatial":[123],"classification,":[126],"such":[127],"properties":[130],"clay":[132],"flocs.":[133]},"counts_by_year":[],"updated_date":"2025-12-25T23:11:45.687758","created_date":"2025-10-10T00:00:00"}
