{"id":"https://openalex.org/W2127022264","doi":"https://doi.org/10.1109/isda.2007.60","title":"Biomass Based Weed-Crop Competitiveness Classification Using Bayesian Networks","display_name":"Biomass Based Weed-Crop Competitiveness Classification Using Bayesian Networks","publication_year":2007,"publication_date":"2007-10-01","ids":{"openalex":"https://openalex.org/W2127022264","doi":"https://doi.org/10.1109/isda.2007.60","mag":"2127022264"},"language":"en","primary_location":{"id":"doi:10.1109/isda.2007.60","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isda.2007.60","pdf_url":null,"source":{"id":"https://openalex.org/S4363608190","display_name":"Seventh International Conference on Intelligent Systems Design and Applications (ISDA 2007)","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":"Seventh International Conference on Intelligent Systems Design and Applications (ISDA 2007)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5070163783","display_name":"Gl\u00e1ucia Maria Bressan","orcid":"https://orcid.org/0000-0001-6996-3129"},"institutions":[{"id":"https://openalex.org/I17974374","display_name":"Universidade de S\u00e3o Paulo","ror":"https://ror.org/036rp1748","country_code":"BR","type":"education","lineage":["https://openalex.org/I17974374"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Glaucia M. Bressan","raw_affiliation_strings":["Depto. de Engenharia El\u00e9trica, Control Laboratory, Universidade de S\u00e1o Paulo, Sao Paulo, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Depto. de Engenharia El\u00e9trica, Control Laboratory, Universidade de S\u00e1o Paulo, Sao Paulo, Brazil","institution_ids":["https://openalex.org/I17974374"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088116219","display_name":"Vilma A. Oliveira","orcid":"https://orcid.org/0000-0001-6078-9515"},"institutions":[{"id":"https://openalex.org/I17974374","display_name":"Universidade de S\u00e3o Paulo","ror":"https://ror.org/036rp1748","country_code":"BR","type":"education","lineage":["https://openalex.org/I17974374"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Vilma A. Oliveira","raw_affiliation_strings":["Depto. de Engenharia El\u00e9trica, Control Laboratory, Universidade de S\u00e1o Paulo, Sao Paulo, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Depto. de Engenharia El\u00e9trica, Control Laboratory, Universidade de S\u00e1o Paulo, Sao Paulo, Brazil","institution_ids":["https://openalex.org/I17974374"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005456217","display_name":"Estevan R. Hruschka","orcid":null},"institutions":[{"id":"https://openalex.org/I177909021","display_name":"Universidade Federal de S\u00e3o Carlos","ror":"https://ror.org/00qdc6m37","country_code":"BR","type":"education","lineage":["https://openalex.org/I177909021"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Estevan R. Hruschka","raw_affiliation_strings":["Depto. de Computa\u00e7\u00e3o, Universidade Federal de S\u00e3o Carlos, Sao Paulo, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Depto. de Computa\u00e7\u00e3o, Universidade Federal de S\u00e3o Carlos, Sao Paulo, Brazil","institution_ids":["https://openalex.org/I177909021"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113765429","display_name":"M. C. Nicoletti","orcid":null},"institutions":[{"id":"https://openalex.org/I177909021","display_name":"Universidade Federal de S\u00e3o Carlos","ror":"https://ror.org/00qdc6m37","country_code":"BR","type":"education","lineage":["https://openalex.org/I177909021"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Maria C. Nicoletti","raw_affiliation_strings":["Depto. de Computa\u00e7\u00e3o, Universidade Federal de S\u00e3o Carlos, Sao Paulo, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Depto. de Computa\u00e7\u00e3o, Universidade Federal de S\u00e3o Carlos, Sao Paulo, Brazil","institution_ids":["https://openalex.org/I177909021"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2226,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.4885763,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"121","last_page":"126"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9966999888420105,"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/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9966999888420105,"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/T10050","display_name":"Multi-Criteria Decision Making","score":0.9333999752998352,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T13058","display_name":"Soil and Land Suitability Analysis","score":0.9114999771118164,"subfield":{"id":"https://openalex.org/subfields/2308","display_name":"Management, Monitoring, Policy and Law"},"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/bayesian-network","display_name":"Bayesian network","score":0.6908917427062988},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6566451787948608},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.6540052890777588},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6171571016311646},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6048099994659424},{"id":"https://openalex.org/keywords/weed","display_name":"Weed","score":0.5790250301361084},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.535385012626648},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4918551445007324},{"id":"https://openalex.org/keywords/bayes-theorem","display_name":"Bayes' theorem","score":0.457785964012146},{"id":"https://openalex.org/keywords/bayes-classifier","display_name":"Bayes classifier","score":0.43379688262939453},{"id":"https://openalex.org/keywords/probabilistic-classification","display_name":"Probabilistic classification","score":0.41461434960365295},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4026678204536438},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.36616644263267517},{"id":"https://openalex.org/keywords/agronomy","display_name":"Agronomy","score":0.17972856760025024},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.0864928662776947}],"concepts":[{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.6908917427062988},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6566451787948608},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.6540052890777588},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6171571016311646},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6048099994659424},{"id":"https://openalex.org/C2775891814","wikidata":"https://www.wikidata.org/wiki/Q101879","display_name":"Weed","level":2,"score":0.5790250301361084},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.535385012626648},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4918551445007324},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.457785964012146},{"id":"https://openalex.org/C185207860","wikidata":"https://www.wikidata.org/wiki/Q17004744","display_name":"Bayes classifier","level":4,"score":0.43379688262939453},{"id":"https://openalex.org/C189119545","wikidata":"https://www.wikidata.org/wiki/Q5128022","display_name":"Probabilistic classification","level":4,"score":0.41461434960365295},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4026678204536438},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36616644263267517},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.17972856760025024},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.0864928662776947},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isda.2007.60","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isda.2007.60","pdf_url":null,"source":{"id":"https://openalex.org/S4363608190","display_name":"Seventh International Conference on Intelligent Systems Design and Applications (ISDA 2007)","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":"Seventh International Conference on Intelligent Systems Design and Applications (ISDA 2007)","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":13,"referenced_works":["https://openalex.org/W1593793857","https://openalex.org/W1974439938","https://openalex.org/W1981956054","https://openalex.org/W1983690667","https://openalex.org/W2026765215","https://openalex.org/W2034980458","https://openalex.org/W2069027711","https://openalex.org/W2134423394","https://openalex.org/W2150817409","https://openalex.org/W2159080219","https://openalex.org/W2159517871","https://openalex.org/W4233891698","https://openalex.org/W4292157289"],"related_works":["https://openalex.org/W1972450020","https://openalex.org/W2996897273","https://openalex.org/W1607432302","https://openalex.org/W83434975","https://openalex.org/W1584413767","https://openalex.org/W2537862391","https://openalex.org/W145653800","https://openalex.org/W2342969114","https://openalex.org/W2122175496","https://openalex.org/W2393473353"],"abstract_inverted_index":{"This":[0],"paper":[1,120],"describes":[2],"the":[3,22,58,73,83,88,94,104,108,113,129,135],"modeling":[4],"of":[5,21,33,60,69,91,97,124,137],"a":[6,15,31,54,62,67,122],"biomass":[7,110,136],"based":[8,13,47],"weed-crop":[9,114],"competitiveness":[10,115],"classification":[11,34],"process,":[12],"on":[14,48],"Bayesian":[16,75,84,130],"network":[17,76,85,131],"classifier.":[18,77],"The":[19,43,78,119],"understandability":[20],"model":[23],"is":[24,46,107,116],"improved":[25],"by":[26,40],"its":[27],"automatic":[28],"translation":[29],"into":[30],"set":[32,68,123],"rules,":[35],"which":[36,112,133],"are":[37,87],"easily":[38],"understood":[39],"human":[41],"beings.":[42],"Bayes":[44],"approach":[45],"empirical":[49],"data":[50],"col-":[51],"lected":[52],"in":[53],"corn-crop":[55],"and":[56,93,100,103],"uses":[57],"concept":[59],"maximum":[61],"posteriori":[63],"probability":[64],"to":[65,81],"extract":[66],"probabilistic":[70],"rules":[71,126],"from":[72,111,128],"induced":[74],"features":[79],"used":[80],"build":[82],"classifier":[86,132],"total":[89],"density":[90],"weeds":[92,102,109],"corresponding":[95],"proportions":[96],"nar-":[98],"row":[99],"broadleaf":[101],"class":[105],"variable":[106],"in-":[117],"ferred.":[118],"presents":[121],"27":[125],"extracted":[127],"classify":[134],"weeds.":[138]},"counts_by_year":[{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}