{"id":"https://openalex.org/W2546616350","doi":"https://doi.org/10.1109/icacci.2016.7732244","title":"ELM variants comparison on applications of time series data forecasting","display_name":"ELM variants comparison on applications of time series data forecasting","publication_year":2016,"publication_date":"2016-09-01","ids":{"openalex":"https://openalex.org/W2546616350","doi":"https://doi.org/10.1109/icacci.2016.7732244","mag":"2546616350"},"language":"en","primary_location":{"id":"doi:10.1109/icacci.2016.7732244","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icacci.2016.7732244","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI)","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/A5090500943","display_name":"Sachin Kumar","orcid":"https://orcid.org/0000-0002-5324-2156"},"institutions":[{"id":"https://openalex.org/I110166357","display_name":"University of Delhi","ror":"https://ror.org/04gzb2213","country_code":"IN","type":"education","lineage":["https://openalex.org/I110166357"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Sachin Kumar","raw_affiliation_strings":["Dept of Computer Science, University of Delhi, Delhi, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept of Computer Science, University of Delhi, Delhi, India","institution_ids":["https://openalex.org/I110166357"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089917679","display_name":"Shobha Rai","orcid":null},"institutions":[{"id":"https://openalex.org/I110166357","display_name":"University of Delhi","ror":"https://ror.org/04gzb2213","country_code":"IN","type":"education","lineage":["https://openalex.org/I110166357"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Shobha Rai","raw_affiliation_strings":["Cluster Innovation Centre University of Delhi, Delhi, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cluster Innovation Centre University of Delhi, Delhi, India","institution_ids":["https://openalex.org/I110166357"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100605814","display_name":"R. P. Singh","orcid":"https://orcid.org/0000-0002-9896-1170"},"institutions":[{"id":"https://openalex.org/I110166357","display_name":"University of Delhi","ror":"https://ror.org/04gzb2213","country_code":"IN","type":"education","lineage":["https://openalex.org/I110166357"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Rampal Singh","raw_affiliation_strings":["Dept of Computer Science, University of Delhi, Delhi, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept of Computer Science, University of Delhi, Delhi, India","institution_ids":["https://openalex.org/I110166357"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017906663","display_name":"Saibal K. Pal","orcid":"https://orcid.org/0000-0003-3297-1605"},"institutions":[{"id":"https://openalex.org/I1340206300","display_name":"Defence Research and Development Organisation","ror":"https://ror.org/05k37v296","country_code":"IN","type":"government","lineage":["https://openalex.org/I1340206300","https://openalex.org/I4210150591"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Saibal K Pal","raw_affiliation_strings":["Scientist \u2018G\u2019, DRDO, Delhi, India","Scientist 'G', DRDO, Delhi, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Scientist \u2018G\u2019, DRDO, Delhi, India","institution_ids":["https://openalex.org/I1340206300"]},{"raw_affiliation_string":"Scientist 'G', DRDO, Delhi, India","institution_ids":["https://openalex.org/I1340206300"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.2082,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.91097437,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1404","last_page":"1409"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":1.0,"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/T12676","display_name":"Machine Learning and ELM","score":1.0,"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/T10320","display_name":"Neural Networks and Applications","score":0.9951000213623047,"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/T10057","display_name":"Face and Expression Recognition","score":0.9872000217437744,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/extreme-learning-machine","display_name":"Extreme learning machine","score":0.8637261390686035},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.655790388584137},{"id":"https://openalex.org/keywords/maxima-and-minima","display_name":"Maxima and minima","score":0.6543958187103271},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6367101073265076},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.633941113948822},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.6118882894515991},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.5333585143089294},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.4895707070827484},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47927019000053406},{"id":"https://openalex.org/keywords/feedforward-neural-network","display_name":"Feedforward neural network","score":0.45413738489151},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.39739474654197693},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3760131895542145},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.329567015171051},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.20180723071098328}],"concepts":[{"id":"https://openalex.org/C2780150128","wikidata":"https://www.wikidata.org/wiki/Q21948731","display_name":"Extreme learning machine","level":3,"score":0.8637261390686035},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.655790388584137},{"id":"https://openalex.org/C186633575","wikidata":"https://www.wikidata.org/wiki/Q845060","display_name":"Maxima and minima","level":2,"score":0.6543958187103271},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6367101073265076},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.633941113948822},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.6118882894515991},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.5333585143089294},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4895707070827484},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47927019000053406},{"id":"https://openalex.org/C47702885","wikidata":"https://www.wikidata.org/wiki/Q5441227","display_name":"Feedforward neural network","level":3,"score":0.45413738489151},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39739474654197693},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3760131895542145},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.329567015171051},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20180723071098328},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"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/icacci.2016.7732244","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icacci.2016.7732244","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI)","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":38,"referenced_works":["https://openalex.org/W320808933","https://openalex.org/W1596717185","https://openalex.org/W1604591429","https://openalex.org/W1606551523","https://openalex.org/W1973485165","https://openalex.org/W1977127140","https://openalex.org/W1989386584","https://openalex.org/W1993717606","https://openalex.org/W1995382443","https://openalex.org/W2026131661","https://openalex.org/W2035740143","https://openalex.org/W2039708501","https://openalex.org/W2042184006","https://openalex.org/W2050099778","https://openalex.org/W2069315453","https://openalex.org/W2075193177","https://openalex.org/W2075846637","https://openalex.org/W2090758866","https://openalex.org/W2095635024","https://openalex.org/W2101674911","https://openalex.org/W2104698839","https://openalex.org/W2108537597","https://openalex.org/W2111072639","https://openalex.org/W2114471530","https://openalex.org/W2119821739","https://openalex.org/W2131836320","https://openalex.org/W2134603844","https://openalex.org/W2141695047","https://openalex.org/W2148446997","https://openalex.org/W2158054309","https://openalex.org/W2168618665","https://openalex.org/W2217896605","https://openalex.org/W2473649147","https://openalex.org/W2545384749","https://openalex.org/W2792298817","https://openalex.org/W4239510810","https://openalex.org/W6636092645","https://openalex.org/W6664426724"],"related_works":["https://openalex.org/W1987504169","https://openalex.org/W2015517331","https://openalex.org/W3146965950","https://openalex.org/W2089434914","https://openalex.org/W2618322250","https://openalex.org/W2072057046","https://openalex.org/W2098841127","https://openalex.org/W2154980374","https://openalex.org/W2040604977","https://openalex.org/W2043923634"],"abstract_inverted_index":{"Extreme":[0],"learning":[1,15,50,98],"machine":[2],"(ELM)":[3],"which":[4],"belongs":[5],"to":[6],"randomized":[7],"algorithm":[8],"categories,":[9],"is":[10],"versatile":[11],"and":[12,35,78,87,92,127],"an":[13,106],"emerging":[14],"algorithm.":[16],"ELM":[17,69,77,132],"has":[18],"been":[19],"developed":[20],"for":[21],"different":[22,66],"application":[23],"starting":[24],"from":[25],"pattern":[26],"recognition,":[27],"function":[28],"estimation,":[29],"regression":[30],"analysis,":[31,34],"time":[32,74,96,124],"series":[33,75,125],"big":[36],"data":[37,126],"analysis":[38],"etc.":[39],"Unlike":[40],"feed":[41,112],"forward":[42,113],"neural":[43,114],"networks":[44,115],"where":[45,81],"slow":[46],"convergence":[47],"rate,":[48],"imprecise":[49],"parameters,":[51],"presence":[52],"of":[53,68,97,103,108,131],"local":[54],"minima":[55],"are":[56,89],"major":[57],"bottles":[58],"neck,":[59],"This":[60],"paper":[61,119],"addresses":[62],"these":[63],"problems":[64],"using":[65],"variants":[67,80,130],"on":[70,122,144],"some":[71],"bench":[72],"mark":[73],"data.":[76],"its":[79],"hidden":[82,110],"nodes":[83],"parameters":[84],"like":[85],"weights":[86,104],"biases":[88],"randomly":[90],"generated":[91],"fixed":[93],"during":[94],"the":[95],"process,":[99],"also":[100],"give":[101],"results":[102],"as":[105],"output":[107],"single":[109],"layer":[111],"(SLFNs)":[116],"analytically.":[117],"The":[118],"performs":[120],"experiments":[121],"two":[123],"demonstrates":[128],"that":[129],"delivers":[133],"good":[134],"performance":[135],"in":[136,139],"generalized":[137],"manner":[138],"several":[140],"cases":[141],"without":[142],"compromising":[143],"accuracy.":[145]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":3}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
