{"id":"https://openalex.org/W4391011686","doi":"https://doi.org/10.1142/s0218126624502025","title":"Ensemble Model for Stock Price Forecasting: MapReduce Framework for Big Data Handling: An Optimal Trained Hybrid Model for Classification","display_name":"Ensemble Model for Stock Price Forecasting: MapReduce Framework for Big Data Handling: An Optimal Trained Hybrid Model for Classification","publication_year":2024,"publication_date":"2024-01-18","ids":{"openalex":"https://openalex.org/W4391011686","doi":"https://doi.org/10.1142/s0218126624502025"},"language":"en","primary_location":{"id":"doi:10.1142/s0218126624502025","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218126624502025","pdf_url":null,"source":{"id":"https://openalex.org/S167602672","display_name":"Journal of Circuits Systems and Computers","issn_l":"0218-1266","issn":["0218-1266","1793-6454"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Circuits, Systems and Computers","raw_type":"journal-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/A5045353459","display_name":"R. Senthamil Selvi","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"R. Senthamil Selvi","raw_affiliation_strings":["Department of Computer Science and Engineering, Saranathan College of Engineering, Venkateswara Nagar, Trichy\u2013Madurai Highway, Panjappur 620012, Tamil Nadu, India"],"raw_orcid":"https://orcid.org/0000-0003-0725-9210","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Saranathan College of Engineering, Venkateswara Nagar, Trichy\u2013Madurai Highway, Panjappur 620012, Tamil Nadu, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033836247","display_name":"V. Sankari","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"V. Sankari","raw_affiliation_strings":["Department of Computer Science and Engineering, K. Ramakrishnan College of Engineering, Samayapuram\u2013Kariyamanickam Road 621112, Tamil Nadu, India"],"raw_orcid":"https://orcid.org/0009-0003-0269-8318","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, K. Ramakrishnan College of Engineering, Samayapuram\u2013Kariyamanickam Road 621112, Tamil Nadu, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103208126","display_name":"N. Ramya","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"N. Ramya","raw_affiliation_strings":["Department of Computer Science and Engineering, Saranathan College of Engineering, Venkateswara Nagar, Trichy\u2013Madurai Highway, Panjappur 620012, Tamil Nadu, India"],"raw_orcid":"https://orcid.org/0000-0002-3899-7833","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Saranathan College of Engineering, Venkateswara Nagar, Trichy\u2013Madurai Highway, Panjappur 620012, Tamil Nadu, India","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101453764","display_name":"M. Selvi","orcid":null},"institutions":[{"id":"https://openalex.org/I43814544","display_name":"Sathyabama Institute of Science and Technology","ror":"https://ror.org/01defpn95","country_code":"IN","type":"education","lineage":["https://openalex.org/I43814544"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"M. Selvi","raw_affiliation_strings":["Department of Computer Science and Engineering, Sathiyabama Institute of Science and Technology, Chennai 600119, Tamil Nadu, India"],"raw_orcid":"https://orcid.org/0000-0003-1175-5655","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Sathiyabama Institute of Science and Technology, Chennai 600119, Tamil Nadu, India","institution_ids":["https://openalex.org/I43814544"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5045353459"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.8968,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.73608626,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":"33","issue":"11","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9995999932289124,"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"}},"topics":[{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9995999932289124,"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/T11918","display_name":"Forecasting Techniques and Applications","score":0.9891999959945679,"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/T14319","display_name":"Currency Recognition and Detection","score":0.9878000020980835,"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/computer-science","display_name":"Computer science","score":0.7489938139915466},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6152594089508057},{"id":"https://openalex.org/keywords/data-pre-processing","display_name":"Data pre-processing","score":0.583446741104126},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.5710229277610779},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.5598021745681763},{"id":"https://openalex.org/keywords/normalization","display_name":"Normalization (sociology)","score":0.5539600849151611},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5376684665679932},{"id":"https://openalex.org/keywords/skewness","display_name":"Skewness","score":0.4840928316116333},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4747907519340515},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4647860527038574},{"id":"https://openalex.org/keywords/kurtosis","display_name":"Kurtosis","score":0.4618903696537018},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4546521008014679},{"id":"https://openalex.org/keywords/database-normalization","display_name":"Database normalization","score":0.43149879574775696},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.43063271045684814},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.10023865103721619},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07984909415245056}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7489938139915466},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6152594089508057},{"id":"https://openalex.org/C10551718","wikidata":"https://www.wikidata.org/wiki/Q5227332","display_name":"Data pre-processing","level":2,"score":0.583446741104126},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.5710229277610779},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.5598021745681763},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.5539600849151611},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5376684665679932},{"id":"https://openalex.org/C122342681","wikidata":"https://www.wikidata.org/wiki/Q330828","display_name":"Skewness","level":2,"score":0.4840928316116333},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4747907519340515},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4647860527038574},{"id":"https://openalex.org/C166963901","wikidata":"https://www.wikidata.org/wiki/Q287251","display_name":"Kurtosis","level":2,"score":0.4618903696537018},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4546521008014679},{"id":"https://openalex.org/C162984825","wikidata":"https://www.wikidata.org/wiki/Q339072","display_name":"Database normalization","level":3,"score":0.43149879574775696},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.43063271045684814},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.10023865103721619},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07984909415245056},{"id":"https://openalex.org/C19165224","wikidata":"https://www.wikidata.org/wiki/Q23404","display_name":"Anthropology","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s0218126624502025","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218126624502025","pdf_url":null,"source":{"id":"https://openalex.org/S167602672","display_name":"Journal of Circuits Systems and Computers","issn_l":"0218-1266","issn":["0218-1266","1793-6454"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Circuits, Systems and Computers","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W2790662215","https://openalex.org/W2907770500","https://openalex.org/W2909459249","https://openalex.org/W2910969563","https://openalex.org/W2914655456","https://openalex.org/W2916088625","https://openalex.org/W2922396237","https://openalex.org/W2941048624","https://openalex.org/W2941074343","https://openalex.org/W2943677129","https://openalex.org/W2954342716","https://openalex.org/W2966492028","https://openalex.org/W3006400770","https://openalex.org/W3017230581","https://openalex.org/W3083912519","https://openalex.org/W3086573485","https://openalex.org/W3115066208","https://openalex.org/W3118270083","https://openalex.org/W3131452730","https://openalex.org/W3165526157","https://openalex.org/W3168104563","https://openalex.org/W3179832096","https://openalex.org/W3182740506","https://openalex.org/W3208656506","https://openalex.org/W4387527434"],"related_works":["https://openalex.org/W4225568567","https://openalex.org/W4286378979","https://openalex.org/W1496883226","https://openalex.org/W4297337052","https://openalex.org/W2028605949","https://openalex.org/W2282665605","https://openalex.org/W3216026256","https://openalex.org/W3129919015","https://openalex.org/W2582603276","https://openalex.org/W4312138714"],"abstract_inverted_index":{"A":[0,16],"number":[1],"of":[2,115,120],"authors":[3],"have":[4],"focused":[5],"on":[6],"this":[7],"study":[8],"to":[9,48,75],"examine":[10],"how":[11],"huge":[12],"data":[13,19,87],"are":[14,71],"perceived.":[15],"novel":[17],"big":[18],"classification":[20,31,83,94],"paradigm":[21],"is":[22,35,45],"introduced":[23],"by":[24,101],"the":[25,39,50,86,89,102,118],"work\u2019s":[26],"preprocessing,":[27],"feature":[28],"extraction":[29],"and":[30,58,65,68,79,129],"techniques.":[32],"Data":[33],"normalization":[34],"carried":[36],"out":[37],"at":[38],"preprocessing":[40],"stage.":[41,91],"The":[42,77,111],"MapReduce":[43],"framework":[44],"then":[46],"utilized":[47],"manage":[49],"massive":[51],"data.":[52],"Statistical":[53],"features":[54,62,70],"(mean,":[55],"median,":[56],"min/max":[57],"SD),":[59],"higher-order":[60],"statistical":[61],"(skewness,":[63],"kurtosis":[64],"enhanced":[66],"entropy),":[67],"correlation-based":[69],"all":[72],"extracted":[73],"prior":[74],"classification.":[76],"Bi-LSTM":[78,127],"deep":[80],"maxout":[81],"hybrid":[82],"model":[84],"classifies":[85],"during":[88],"reduction":[90],"To":[92],"assure":[93],"accuracy,":[95],"training":[96],"will":[97],"also":[98],"be":[99],"deployed":[100],"new":[103],"Hybrid":[104],"Butterfly":[105],"Positioned":[106],"Coot":[107],"Optimization":[108],"(HBPCO)":[109],"algorithm.":[110],"proposed":[112],"method\u2019s":[113],"accuracy":[114],"97.45%":[116],"beats":[117],"methods":[119],"NN":[121],"(85.13%),":[122],"CNN":[123],"(83.78%),":[124],"RNN":[125],"(78.37%),":[126],"(82.43%)":[128],"SVM":[130],"(87.83%).":[131]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-05-21T09:19:25.381259","created_date":"2025-10-10T00:00:00"}
