{"id":"https://openalex.org/W3167177963","doi":"https://doi.org/10.1145/3463677.3463713","title":"Using Artificial Intelligence Techniques for Evidence-Based Decision Making in Government: Random Forest and Deep Neural Network Classification for Predicting Harmful Algal Blooms in New York State","display_name":"Using Artificial Intelligence Techniques for Evidence-Based Decision Making in Government: Random Forest and Deep Neural Network Classification for Predicting Harmful Algal Blooms in New York State","publication_year":2021,"publication_date":"2021-06-09","ids":{"openalex":"https://openalex.org/W3167177963","doi":"https://doi.org/10.1145/3463677.3463713","mag":"3167177963"},"language":"en","primary_location":{"id":"doi:10.1145/3463677.3463713","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3463677.3463713","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"DG.O2021: The 22nd Annual International Conference on Digital Government Research","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/A5025049015","display_name":"Yongjin Choi","orcid":"https://orcid.org/0000-0002-4085-062X"},"institutions":[{"id":"https://openalex.org/I113508548","display_name":"Albany State University","ror":"https://ror.org/01vme4277","country_code":"US","type":"education","lineage":["https://openalex.org/I113508548"]},{"id":"https://openalex.org/I392282","display_name":"University at Albany, State University of New York","ror":"https://ror.org/012zs8222","country_code":"US","type":"education","lineage":["https://openalex.org/I392282"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yongjin Choi","raw_affiliation_strings":["University at Albany, State University of New York, United States"],"affiliations":[{"raw_affiliation_string":"University at Albany, State University of New York, United States","institution_ids":["https://openalex.org/I113508548","https://openalex.org/I392282"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073085531","display_name":"Ramon Gil-Garcia","orcid":null},"institutions":[{"id":"https://openalex.org/I392282","display_name":"University at Albany, State University of New York","ror":"https://ror.org/012zs8222","country_code":"US","type":"education","lineage":["https://openalex.org/I392282"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ramon Gil-Garcia","raw_affiliation_strings":["University at Albany, State University of New York & Universidad de las Americas Puebla, United States"],"affiliations":[{"raw_affiliation_string":"University at Albany, State University of New York & Universidad de las Americas Puebla, United States","institution_ids":["https://openalex.org/I392282"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045911582","display_name":"Oguz M. Aranay","orcid":"https://orcid.org/0000-0002-9284-116X"},"institutions":[{"id":"https://openalex.org/I113508548","display_name":"Albany State University","ror":"https://ror.org/01vme4277","country_code":"US","type":"education","lineage":["https://openalex.org/I113508548"]},{"id":"https://openalex.org/I392282","display_name":"University at Albany, State University of New York","ror":"https://ror.org/012zs8222","country_code":"US","type":"education","lineage":["https://openalex.org/I392282"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Oguz Aranay","raw_affiliation_strings":["University at Albany, State University of New York & University of Kirkuk, United States"],"affiliations":[{"raw_affiliation_string":"University at Albany, State University of New York & University of Kirkuk, United States","institution_ids":["https://openalex.org/I113508548","https://openalex.org/I392282"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050111642","display_name":"Brian C. Burke","orcid":null},"institutions":[{"id":"https://openalex.org/I113508548","display_name":"Albany State University","ror":"https://ror.org/01vme4277","country_code":"US","type":"education","lineage":["https://openalex.org/I113508548"]},{"id":"https://openalex.org/I392282","display_name":"University at Albany, State University of New York","ror":"https://ror.org/012zs8222","country_code":"US","type":"education","lineage":["https://openalex.org/I392282"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Brian Burke","raw_affiliation_strings":["University at Albany, State University of New York, United States"],"affiliations":[{"raw_affiliation_string":"University at Albany, State University of New York, United States","institution_ids":["https://openalex.org/I113508548","https://openalex.org/I392282"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036980035","display_name":"Derek Werthmuller","orcid":"https://orcid.org/0009-0007-9719-6087"},"institutions":[{"id":"https://openalex.org/I392282","display_name":"University at Albany, State University of New York","ror":"https://ror.org/012zs8222","country_code":"US","type":"education","lineage":["https://openalex.org/I392282"]},{"id":"https://openalex.org/I113508548","display_name":"Albany State University","ror":"https://ror.org/01vme4277","country_code":"US","type":"education","lineage":["https://openalex.org/I113508548"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Derek Werthmuller","raw_affiliation_strings":["University at Albany, State University of New York, United States"],"affiliations":[{"raw_affiliation_string":"University at Albany, State University of New York, United States","institution_ids":["https://openalex.org/I113508548","https://openalex.org/I392282"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5025049015"],"corresponding_institution_ids":["https://openalex.org/I113508548","https://openalex.org/I392282"],"apc_list":null,"apc_paid":null,"fwci":1.0721,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.80397533,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"27","last_page":"37"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11891","display_name":"Big Data and Business Intelligence","score":0.8773999810218811,"subfield":{"id":"https://openalex.org/subfields/1404","display_name":"Management Information Systems"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11891","display_name":"Big Data and Business Intelligence","score":0.8773999810218811,"subfield":{"id":"https://openalex.org/subfields/1404","display_name":"Management Information Systems"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10895","display_name":"Species Distribution and Climate Change","score":0.8216999769210815,"subfield":{"id":"https://openalex.org/subfields/2302","display_name":"Ecological Modeling"},"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/T12120","display_name":"Air Quality Monitoring and Forecasting","score":0.7825999855995178,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6906876564025879},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.6451519727706909},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6375351548194885},{"id":"https://openalex.org/keywords/government","display_name":"Government (linguistics)","score":0.6183018088340759},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5854701399803162},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5742527842521667},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.4598023295402527},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.38330399990081787}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6906876564025879},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.6451519727706909},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6375351548194885},{"id":"https://openalex.org/C2778137410","wikidata":"https://www.wikidata.org/wiki/Q2732820","display_name":"Government (linguistics)","level":2,"score":0.6183018088340759},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5854701399803162},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5742527842521667},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.4598023295402527},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.38330399990081787},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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:10.1145/3463677.3463713","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3463677.3463713","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"DG.O2021: The 22nd Annual International Conference on Digital Government Research","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":51,"referenced_works":["https://openalex.org/W177171801","https://openalex.org/W1500801596","https://openalex.org/W1680392829","https://openalex.org/W1789155650","https://openalex.org/W1972877970","https://openalex.org/W1975216592","https://openalex.org/W1977168270","https://openalex.org/W1978187432","https://openalex.org/W1978424046","https://openalex.org/W2011048691","https://openalex.org/W2011577789","https://openalex.org/W2014134870","https://openalex.org/W2023368079","https://openalex.org/W2059705044","https://openalex.org/W2068298920","https://openalex.org/W2101241669","https://openalex.org/W2125303562","https://openalex.org/W2134466521","https://openalex.org/W2136922672","https://openalex.org/W2138631674","https://openalex.org/W2142599319","https://openalex.org/W2148426523","https://openalex.org/W2156555131","https://openalex.org/W2156930128","https://openalex.org/W2165036418","https://openalex.org/W2346905224","https://openalex.org/W2513202618","https://openalex.org/W2576404523","https://openalex.org/W2611026542","https://openalex.org/W2766452046","https://openalex.org/W2766806535","https://openalex.org/W2787887017","https://openalex.org/W2799757121","https://openalex.org/W2809190938","https://openalex.org/W2887752602","https://openalex.org/W2913323966","https://openalex.org/W2919115771","https://openalex.org/W2979808541","https://openalex.org/W2979906316","https://openalex.org/W2997920084","https://openalex.org/W3003800676","https://openalex.org/W3015520318","https://openalex.org/W3031348858","https://openalex.org/W3048427347","https://openalex.org/W3049338919","https://openalex.org/W3080671792","https://openalex.org/W3085162807","https://openalex.org/W3085627532","https://openalex.org/W3106481053","https://openalex.org/W4206634639","https://openalex.org/W4251443534"],"related_works":["https://openalex.org/W3193043704","https://openalex.org/W4394984040","https://openalex.org/W4366990902","https://openalex.org/W4317732970","https://openalex.org/W4388550696","https://openalex.org/W4321636153","https://openalex.org/W4313289487","https://openalex.org/W4384470695","https://openalex.org/W3134840015","https://openalex.org/W4366979180"],"abstract_inverted_index":{"Advances":[0],"in":[1,89,117,152,220],"artificial":[2,136],"intelligence":[3,137],"techniques":[4,248],"have":[5,62,82,249],"shown":[6],"tremendous":[7],"potential":[8,134,251],"as":[9],"a":[10,85],"decision":[11],"support":[12],"tool":[13],"for":[14,218,233],"government":[15,129,235],"agencies.":[16],"However,":[17,93],"recent":[18],"studies":[19],"typically":[20],"highlight":[21],"the":[22,37,90,94,102,110,133,140,186,189,192,239,250],"combination":[23],"of":[24,39,78,99,135,142,188,241],"large-scale":[25],"datasets":[26,168],"and":[27,51,58,68,96,101,127,147,172,179],"high-performance":[28],"computing":[29],"technologies,":[30],"which":[31],"is":[32],"frequently":[33],"far":[34],"away":[35],"from":[36,166],"reality":[38],"many":[40],"public":[41,206],"agencies":[42,207],"that":[43,55,176,201,208],"still":[44,230],"heavily":[45],"rely":[46],"on":[47,106],"their":[48],"legacy":[49,222],"systems":[50],"labor-intensive":[52],"practices.":[53],"Using":[54],"non-ideal":[56],"organizational":[57],"technical":[59],"infrastructure,":[60],"they":[61],"to":[63,122,211,213,252],"face":[64],"very":[65],"complex":[66],"problems":[67],"propose":[69],"policy":[70],"solutions.":[71],"Harmful":[72],"algal":[73],"blooms":[74],"(HABs)":[75],"are":[76,209,243],"one":[77],"such":[79],"problems.":[80],"HABs":[81,154,162,214],"increasingly":[83],"become":[84],"serious":[86],"environmental":[87],"issue":[88],"United":[91],"States.":[92],"rapid":[95],"sporadic":[97],"growth":[98],"algae":[100],"current":[103,128],"standard":[104],"relying":[105],"manual":[107,156],"sampling":[108,157],"weaken":[109],"agencies'":[111],"response.":[112],"To":[113],"overcome":[114],"this":[115,118,202],"limitation,":[116],"study,":[119],"we":[120,174,199],"attempt":[121],"bridge":[123],"advanced":[124],"AI":[125,247],"technologies":[126],"practice":[130],"by":[131,138],"examining":[132],"comparing":[139],"performance":[141],"linear":[143],"probability,":[144],"random":[145,177],"forest,":[146],"deep":[148,180],"neural":[149,181],"network":[150,182],"algorithms":[151,184],"predicting":[153],"with":[155,164,215,226],"data.":[158],"By":[159],"integrating":[160],"manually-sampled":[161],"data":[163,228],"predictors":[165],"publicly-available":[167],"(land":[169],"use,":[170],"weather,":[171],"drought),":[173],"demonstrate":[175],"forest":[178],"(DNN)":[183],"improve":[185,253],"specificity":[187],"prediction,":[190],"increasing":[191],"true":[193],"negative":[194],"rate.":[195],"Albeit":[196],"not":[197,244],"ideal,":[198],"believe":[200],"approach":[203],"can":[204],"benefit":[205],"forced":[210],"respond":[212],"limited":[216,227],"resources":[217],"investing":[219],"improving":[221],"systems.":[223],"Accurate":[224],"prediction":[225],"could":[229],"be":[231],"useful":[232],"certain":[234],"decisions,":[236],"even":[237],"when":[238],"mechanisms":[240],"causality":[242],"totally":[245],"clear.":[246],"these":[254],"predictive":[255],"capabilities.":[256]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}