{"id":"https://openalex.org/W4391936746","doi":"https://doi.org/10.1109/icacic59454.2023.10434951","title":"Multivariate Time Series Forecasting to Forecast Weight Dynamics","display_name":"Multivariate Time Series Forecasting to Forecast Weight Dynamics","publication_year":2023,"publication_date":"2023-12-07","ids":{"openalex":"https://openalex.org/W4391936746","doi":"https://doi.org/10.1109/icacic59454.2023.10434951"},"language":"en","primary_location":{"id":"doi:10.1109/icacic59454.2023.10434951","doi":"https://doi.org/10.1109/icacic59454.2023.10434951","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icacic59454.2023.10434951","pdf_url":null,"source":{"id":"https://openalex.org/S7407097565","display_name":"International Conference on Advances in Computational Intelligence and Communication (ICACIC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 Second International Conference on Advances in Computational Intelligence and Communication (ICACIC)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"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/A5007440181","display_name":"Semanto Mondal","orcid":"https://orcid.org/0009-0000-2306-4478","observed_orcids":["https://orcid.org/0009-0000-2306-4478"]},"institutions":[{"id":"https://openalex.org/I71267560","display_name":"University of Naples Federico II","ror":"https://ror.org/05290cv24","country_code":"IT","type":"education","lineage":["https://openalex.org/I71267560"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Semanto Mondal","raw_affiliation_strings":["University of Naples Federico II,Data Science,Naples,Italy","Data Science, University of Naples Federico II, Naples, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Naples Federico II,Data Science,Naples,Italy","institution_ids":["https://openalex.org/I71267560"]},{"raw_affiliation_string":"Data Science, University of Naples Federico II, Naples, Italy","institution_ids":["https://openalex.org/I71267560"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Prakash Srinivasan","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I71267560","display_name":"University of Naples Federico II","ror":"https://ror.org/05290cv24","country_code":"IT","type":"education","lineage":["https://openalex.org/I71267560"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Prakash Srinivasan","raw_affiliation_strings":["University of Naples Federico II,Data Science,Naples,Italy","Data Science, University of Naples Federico II, Naples, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Naples Federico II,Data Science,Naples,Italy","institution_ids":["https://openalex.org/I71267560"]},{"raw_affiliation_string":"Data Science, University of Naples Federico II, Naples, Italy","institution_ids":["https://openalex.org/I71267560"]}]},{"author_position":"last","author":{"id":null,"display_name":"Rajib Chandra Ghosh","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I71267560","display_name":"University of Naples Federico II","ror":"https://ror.org/05290cv24","country_code":"IT","type":"education","lineage":["https://openalex.org/I71267560"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Rajib Chandra Ghosh","raw_affiliation_strings":["University of Naples Federico II,Data Science,Naples,Italy","Data Science, University of Naples Federico II, Naples, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Naples Federico II,Data Science,Naples,Italy","institution_ids":["https://openalex.org/I71267560"]},{"raw_affiliation_string":"Data Science, University of Naples Federico II, Naples, Italy","institution_ids":["https://openalex.org/I71267560"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I71267560"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"4","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.8978999853134155,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.8978999853134155,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11918","display_name":"Forecasting Techniques and Applications","score":0.08590000122785568,"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/T11326","display_name":"Stock Market Forecasting Methods","score":0.013799999840557575,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/multivariate-time-series-forecasting","display_name":"multivariate time series forecasting","score":0.9150000214576721},{"id":"https://openalex.org/keywords/lstm","display_name":"LSTM","score":0.7020000219345093},{"id":"https://openalex.org/keywords/feature-selection","display_name":"feature selection","score":0.8149999976158142},{"id":"https://openalex.org/keywords/feature-engineering","display_name":"feature engineering","score":0.7059999704360962},{"id":"https://openalex.org/keywords/lag-length-selection","display_name":"lag selection","score":0.6840000152587891},{"id":"https://openalex.org/keywords/insect-population-dynamics","display_name":"insect population dynamics","score":0.824999988079071}],"concepts":[{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.8268429040908813},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.6725131869316101},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.6343590617179871},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.592141330242157},{"id":"https://openalex.org/C145912823","wikidata":"https://www.wikidata.org/wiki/Q113558","display_name":"Dynamics (music)","level":2,"score":0.4429870843887329},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.3944039046764374},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3853638172149658},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32069021463394165},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1793607771396637},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.07918038964271545},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icacic59454.2023.10434951","doi":"https://doi.org/10.1109/icacic59454.2023.10434951","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icacic59454.2023.10434951","pdf_url":null,"source":{"id":"https://openalex.org/S7407097565","display_name":"International Conference on Advances in Computational Intelligence and Communication (ICACIC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 Second International Conference on Advances in Computational Intelligence and Communication (ICACIC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W1975994995","https://openalex.org/W2266306456","https://openalex.org/W2330820318","https://openalex.org/W2336452334","https://openalex.org/W2600746833","https://openalex.org/W3112498453","https://openalex.org/W3125004892","https://openalex.org/W3160826979","https://openalex.org/W4226331723","https://openalex.org/W4317356564"],"related_works":["https://openalex.org/W4392811828","https://openalex.org/W4405184523","https://openalex.org/W4386098401","https://openalex.org/W4416251892","https://openalex.org/W4410249992","https://openalex.org/W4399112852","https://openalex.org/W2963558246","https://openalex.org/W4401808026","https://openalex.org/W7162428151","https://openalex.org/W7131391403"],"abstract_inverted_index":{"This":[0,216],"paper":[1,217],"represents":[2],"a":[3,69,120],"multivariate":[4,223,266],"time":[5,55,76,90,224,267],"series":[6,56,77,91,225,268],"forecasting":[7,128,226],"approach":[8],"to":[9,79,106,185,211,219,262],"predict":[10],"the":[11,24,28,32,36,42,54,89,94,108,115,130,178,187,193,200,208,213,220,228,256],"weight":[12,117,132],"dynamics":[13],"of":[14,27,41,129,199,222,230],"an":[15,112],"insect":[16,231,247],"colony.":[17],"In":[18],"this":[19,46],"paper,":[20],"we":[21,48,66,122],"are":[22],"predicting":[23],"Colony":[25],"Weight":[26],"Insect":[29],"which":[30,74,191],"has":[31,204],"main":[33],"impact":[34,113],"on":[35,53,114],"growth":[37],"and":[38,61,98,151,251],"overall":[39,252],"health":[40],"insects.":[43],"To":[44],"accomplish":[45],"task,":[47],"have":[49,67,102,111,123,182,237,243],"performed":[50,105,124],"extensive":[51],"preprocessing":[52],"data,":[57],"ensuring":[58],"data":[59,135],"quality":[60],"suitability":[62],"for":[63,133,245],"analysis.":[64],"Overall,":[65],"conducted":[68],"high-level":[70],"Exploratory":[71],"Data":[72],"Analysis":[73],"covers":[75],"analysis":[78],"identify":[80],"different":[81],"patterns":[82],"as":[83,85,142,157,166,171,173],"well":[84,172],"trends":[86],"present":[87],"in":[88,227],"data.":[92],"Following":[93],"EDA,":[95],"Feature":[96,99],"Engineering":[97],"Selection":[100],"techniques":[101,140,155],"also":[103],"been":[104,183,205,238],"find":[107,186,212],"features":[109],"that":[110,236,241],"colony":[116,131,232],"feature.":[118],"As":[119],"follow-up,":[121],"Multivariate":[125],"Time":[126,137],"Series":[127,138],"future":[134],"with":[136,147,152,177,207],"Forecasting":[139],"such":[141,156,165],"Vector":[143],"Autoregressive":[144],"moving":[145],"average":[146],"exogenous":[148],"regressors":[149],"(VARMAX)":[150],"Deep":[153],"Learning":[154],"Long":[158],"Short-Term":[159],"Memory":[160],"(LSTM).":[161],"Several":[162],"statistical":[163],"parameters":[164],"AIC":[167],"score,":[168],"BIC":[169],"score":[170],"MSE":[174],"value":[175,190],"along":[176],"grid":[179],"search":[180],"method":[181],"utilized":[184],"optimal":[188],"lag":[189],"affects":[192],"model":[194,203,210],"performance":[195,198],"significantly.":[196],"The":[197],"black":[201],"box":[202],"compared":[206],"interpretable":[209],"best":[214],"outcome.":[215],"contributes":[218],"field":[221],"context":[229],"dynamics.":[233],"Various":[234],"insights":[235],"gained":[239],"from":[240],"study":[242],"implications":[244],"understanding":[246],"behaviour,":[248],"population":[249],"dynamics,":[250],"ecosystem":[253],"health.":[254],"Furthermore,":[255],"proposed":[257],"methodology":[258],"can":[259],"be":[260],"extended":[261],"other":[263],"domains":[264],"involving":[265],"forecasting.":[269]},"counts_by_year":[],"updated_date":"2026-10-26T11:51:55.731654","created_date":"2024-02-20T00:00:00"}
