{"id":"https://openalex.org/W4404032413","doi":"https://doi.org/10.1109/icccnt61001.2024.10726002","title":"Rainfall Prediction Enhancement Using SMOTE and Machine Learning Algorithms","display_name":"Rainfall Prediction Enhancement Using SMOTE and Machine Learning Algorithms","publication_year":2024,"publication_date":"2024-06-24","ids":{"openalex":"https://openalex.org/W4404032413","doi":"https://doi.org/10.1109/icccnt61001.2024.10726002"},"language":"en","primary_location":{"id":"doi:10.1109/icccnt61001.2024.10726002","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icccnt61001.2024.10726002","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT)","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/A5101887570","display_name":"Rohit Kumar","orcid":"https://orcid.org/0000-0001-6910-7998"},"institutions":[{"id":"https://openalex.org/I81556334","display_name":"Amrita Vishwa Vidyapeetham","ror":"https://ror.org/03am10p12","country_code":"IN","type":"education","lineage":["https://openalex.org/I81556334"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"R Hemanth Kumar","raw_affiliation_strings":["Amrita Vishwa Vidyapeetham,Amrita School of Computing,Department of Computer Science and Engineering,Bengaluru,India"],"affiliations":[{"raw_affiliation_string":"Amrita Vishwa Vidyapeetham,Amrita School of Computing,Department of Computer Science and Engineering,Bengaluru,India","institution_ids":["https://openalex.org/I81556334"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024945761","display_name":"Bhawesh Prasad","orcid":"https://orcid.org/0000-0002-2302-1440"},"institutions":[{"id":"https://openalex.org/I81556334","display_name":"Amrita Vishwa Vidyapeetham","ror":"https://ror.org/03am10p12","country_code":"IN","type":"education","lineage":["https://openalex.org/I81556334"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"B Vishnu Prasad","raw_affiliation_strings":["Amrita Vishwa Vidyapeetham,Amrita School of Computing,Department of Computer Science and Engineering,Bengaluru,India"],"affiliations":[{"raw_affiliation_string":"Amrita Vishwa Vidyapeetham,Amrita School of Computing,Department of Computer Science and Engineering,Bengaluru,India","institution_ids":["https://openalex.org/I81556334"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053431042","display_name":"Himanshu Yadav","orcid":"https://orcid.org/0000-0002-1145-3238"},"institutions":[{"id":"https://openalex.org/I81556334","display_name":"Amrita Vishwa Vidyapeetham","ror":"https://ror.org/03am10p12","country_code":"IN","type":"education","lineage":["https://openalex.org/I81556334"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Himanshu Yadav","raw_affiliation_strings":["Amrita Vishwa Vidyapeetham,Amrita School of Computing,Department of Computer Science and Engineering,Bengaluru,India"],"affiliations":[{"raw_affiliation_string":"Amrita Vishwa Vidyapeetham,Amrita School of Computing,Department of Computer Science and Engineering,Bengaluru,India","institution_ids":["https://openalex.org/I81556334"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038866834","display_name":"Manju Venugopalan","orcid":"https://orcid.org/0000-0001-9325-8948"},"institutions":[{"id":"https://openalex.org/I81556334","display_name":"Amrita Vishwa Vidyapeetham","ror":"https://ror.org/03am10p12","country_code":"IN","type":"education","lineage":["https://openalex.org/I81556334"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Manju Venugopalan","raw_affiliation_strings":["Amrita Vishwa Vidyapeetham,Amrita School of Computing,Department of Computer Science and Engineering,Bengaluru,India"],"affiliations":[{"raw_affiliation_string":"Amrita Vishwa Vidyapeetham,Amrita School of Computing,Department of Computer Science and Engineering,Bengaluru,India","institution_ids":["https://openalex.org/I81556334"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101887570"],"corresponding_institution_ids":["https://openalex.org/I81556334"],"apc_list":null,"apc_paid":null,"fwci":0.6531,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.66280954,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":99},"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/T11490","display_name":"Hydrological Forecasting Using AI","score":0.9552000164985657,"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"}},"topics":[{"id":"https://openalex.org/T11490","display_name":"Hydrological Forecasting Using AI","score":0.9552000164985657,"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":0.724562406539917},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5784493088722229},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5204442143440247},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.49096444249153137}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.724562406539917},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5784493088722229},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5204442143440247},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.49096444249153137}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icccnt61001.2024.10726002","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icccnt61001.2024.10726002","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.800000011920929,"id":"https://metadata.un.org/sdg/13","display_name":"Climate action"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W2900750130","https://openalex.org/W2929929078","https://openalex.org/W2956581425","https://openalex.org/W2998567488","https://openalex.org/W3009468105","https://openalex.org/W3047021033","https://openalex.org/W3096798174","https://openalex.org/W3211539727","https://openalex.org/W3213714946","https://openalex.org/W4206835219","https://openalex.org/W4293057005","https://openalex.org/W4297314621","https://openalex.org/W4388936866","https://openalex.org/W4388937884","https://openalex.org/W4388938317","https://openalex.org/W4392063011","https://openalex.org/W6795337771","https://openalex.org/W6809821057","https://openalex.org/W6856875739","https://openalex.org/W6862364543"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"Rainfall":[0],"prediction":[1,170],"is":[2,37,88,102],"not":[3,103],"an":[4,77,84,110,114,131],"easy":[5],"task":[6],"when":[7],"utilizing":[8],"conventional":[9,169],"approaches.":[10],"For":[11],"many":[12],"stakeholders,":[13],"including":[14],"people":[15],"planning":[16],"their":[17,22,32],"daily":[18],"lives,":[19],"farmers":[20],"caring":[21],"crop,":[23],"and":[24,70,75,94,130,158],"fishermen":[25],"who":[26],"depend":[27],"on":[28],"the":[29,92,98,136,141],"weather":[30],"for":[31,80,90],"livelihood,":[33],"accurate":[34,157],"rainfall":[35,40,81,101,163],"forecast":[36],"essential.":[38],"Predicting":[39],"more":[41],"accurately":[42],"has":[43],"been":[44],"a":[45,104,120,125],"promising":[46],"use":[47],"of":[48,97,117,122,127,133],"machine":[49,147],"learning":[50,148],"(ML)":[51,149],"models":[52,150],"in":[53,155],"recent":[54],"years.":[55],"Our":[56],"proposed":[57],"framework":[58],"suggests":[59],"using":[60],"classification":[61],"techniques":[62],"like":[63],"Random":[64,137],"Forest,":[65],"K-Nearest":[66],"Neighbors":[67],"(KNN)":[68],"classifier,":[69],"Decision":[71],"Tree":[72],"to":[73,109],"construct":[74],"implement":[76],"ML":[78],"model":[79],"prediction.":[82],"SMOTE,":[83],"efficient":[85],"data-balancing":[86],"technique":[87],"used":[89,154],"balancing":[91],"minority":[93],"majority":[95],"classes":[96],"data,":[99],"as":[100],"uniformly":[105],"distributed":[106],"event,":[107],"leading":[108],"imbalanced":[111],"dataset.":[112],"With":[113],"astounding":[115],"F1-score":[116],"around":[118],"0.91,":[119,135],"precision":[121],"about":[123,128],"0.89,":[124],"recall":[126],"0.94,":[129],"accuracy":[132],"roughly":[134],"Forest":[138],"classifier":[139],"outperformed":[140],"others.":[142],"These":[143],"results":[144],"demonstrate":[145],"how":[146],"could":[151],"possibly":[152],"be":[153],"producing":[156],"depewhich":[159],"are":[160],"effective":[161],"forndable":[162],"forecasts,":[164],"showing":[165],"significant":[166],"improvements":[167],"over":[168],"techniques.":[171]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2}],"updated_date":"2025-12-21T01:58:51.020947","created_date":"2025-10-10T00:00:00"}
