{"id":"https://openalex.org/W4360585510","doi":"https://doi.org/10.1109/ic3i56241.2022.10072956","title":"Analysis of Stock Market Value Prediction using Simple Novel Long Short Term Memory Algorithm in Comparison with Back Propagation Algorithm for Increased Accuracy Rate","display_name":"Analysis of Stock Market Value Prediction using Simple Novel Long Short Term Memory Algorithm in Comparison with Back Propagation Algorithm for Increased Accuracy Rate","publication_year":2022,"publication_date":"2022-12-14","ids":{"openalex":"https://openalex.org/W4360585510","doi":"https://doi.org/10.1109/ic3i56241.2022.10072956"},"language":"en","primary_location":{"id":"doi:10.1109/ic3i56241.2022.10072956","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ic3i56241.2022.10072956","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 5th International Conference on Contemporary Computing and Informatics (IC3I)","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/A5054402659","display_name":"N. Jaswanth Reddy","orcid":null},"institutions":[{"id":"https://openalex.org/I85461943","display_name":"Saveetha University","ror":"https://ror.org/0034me914","country_code":"IN","type":"education","lineage":["https://openalex.org/I85461943"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"N. Jaswanth Reddy","raw_affiliation_strings":["Saveetha Institute of Medical And Technical Sciences Saveetha University,Saveetha School of Engineering,Department of Computer Science and Engineering,Chennai,Tamilnadu,India","Department of Computer Science and Engineering, Saveetha School of Engineering, Saveetha Institute of Medical And Technical Sciences Saveetha University, Chennai, Tamilnadu, India"],"affiliations":[{"raw_affiliation_string":"Saveetha Institute of Medical And Technical Sciences Saveetha University,Saveetha School of Engineering,Department of Computer Science and Engineering,Chennai,Tamilnadu,India","institution_ids":["https://openalex.org/I85461943"]},{"raw_affiliation_string":"Department of Computer Science and Engineering, Saveetha School of Engineering, Saveetha Institute of Medical And Technical Sciences Saveetha University, Chennai, Tamilnadu, India","institution_ids":["https://openalex.org/I85461943"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5052946464","display_name":"K. Jaisharma","orcid":null},"institutions":[{"id":"https://openalex.org/I85461943","display_name":"Saveetha University","ror":"https://ror.org/0034me914","country_code":"IN","type":"education","lineage":["https://openalex.org/I85461943"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"K Jaisharma","raw_affiliation_strings":["Saveetha Institute of Medical And Technical Sciences Saveetha University,Saveetha School of Engineering,Department of Computer Science and Engineering,Chennai,Tamilnadu,India","Department of Computer Science and Engineering, Saveetha School of Engineering, Saveetha Institute of Medical And Technical Sciences Saveetha University, Chennai, Tamilnadu, India"],"affiliations":[{"raw_affiliation_string":"Saveetha Institute of Medical And Technical Sciences Saveetha University,Saveetha School of Engineering,Department of Computer Science and Engineering,Chennai,Tamilnadu,India","institution_ids":["https://openalex.org/I85461943"]},{"raw_affiliation_string":"Department of Computer Science and Engineering, Saveetha School of Engineering, Saveetha Institute of Medical And Technical Sciences Saveetha University, Chennai, Tamilnadu, India","institution_ids":["https://openalex.org/I85461943"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5054402659"],"corresponding_institution_ids":["https://openalex.org/I85461943"],"apc_list":null,"apc_paid":null,"fwci":0.4909,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.69234644,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"867","last_page":"870"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9994999766349792,"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":0.9994999766349792,"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/T10320","display_name":"Neural Networks and Applications","score":0.9704999923706055,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9581999778747559,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/backpropagation","display_name":"Backpropagation","score":0.8286404609680176},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.8075544834136963},{"id":"https://openalex.org/keywords/stock-market","display_name":"Stock market","score":0.5738019943237305},{"id":"https://openalex.org/keywords/long-short-term-memory","display_name":"Long short term memory","score":0.4985237121582031},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.47758176922798157},{"id":"https://openalex.org/keywords/stock","display_name":"Stock (firearms)","score":0.4290620684623718},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.35105791687965393},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2373754382133484},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.22778943181037903}],"concepts":[{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.8286404609680176},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.8075544834136963},{"id":"https://openalex.org/C2780299701","wikidata":"https://www.wikidata.org/wiki/Q475000","display_name":"Stock market","level":3,"score":0.5738019943237305},{"id":"https://openalex.org/C133488467","wikidata":"https://www.wikidata.org/wiki/Q6673524","display_name":"Long short term memory","level":4,"score":0.4985237121582031},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.47758176922798157},{"id":"https://openalex.org/C204036174","wikidata":"https://www.wikidata.org/wiki/Q909380","display_name":"Stock (firearms)","level":2,"score":0.4290620684623718},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.35105791687965393},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2373754382133484},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.22778943181037903},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","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/C2780762169","wikidata":"https://www.wikidata.org/wiki/Q5905368","display_name":"Horse","level":2,"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/ic3i56241.2022.10072956","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ic3i56241.2022.10072956","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 5th International Conference on Contemporary Computing and Informatics (IC3I)","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":24,"referenced_works":["https://openalex.org/W1680797894","https://openalex.org/W2146130211","https://openalex.org/W2784247833","https://openalex.org/W2791901654","https://openalex.org/W2794343888","https://openalex.org/W2916760211","https://openalex.org/W2941116068","https://openalex.org/W2941780884","https://openalex.org/W2981601776","https://openalex.org/W2982335240","https://openalex.org/W2996820742","https://openalex.org/W3000164981","https://openalex.org/W3029781783","https://openalex.org/W3040099731","https://openalex.org/W3083985116","https://openalex.org/W3095101245","https://openalex.org/W3129806041","https://openalex.org/W3133794177","https://openalex.org/W3137665520","https://openalex.org/W3164870412","https://openalex.org/W3209227626","https://openalex.org/W4242084824","https://openalex.org/W4244042700","https://openalex.org/W6637349233"],"related_works":["https://openalex.org/W4239286941","https://openalex.org/W2088845016","https://openalex.org/W589102260","https://openalex.org/W1966421350","https://openalex.org/W2051487156","https://openalex.org/W1868434454","https://openalex.org/W4366985237","https://openalex.org/W4367365565","https://openalex.org/W2810569973","https://openalex.org/W2370669686"],"abstract_inverted_index":{"A":[0],"comparative":[1],"study":[2],"of":[3,13],"improved":[4],"accuracy":[5,68,77,119],"using":[6,43,52],"Simple":[7],"Novel":[8],"Long":[9],"Short-Term":[10],"Memory":[11],"(SNLSTM)":[12],"stock":[14,27,112],"market":[15,28,113],"prediction":[16],"along":[17],"with":[18],"Back":[19,35,59,81,123],"Propagation":[20,36,60,82],"(BP),":[21],"to":[22,80,94],"predict":[23],"values":[24],"in":[25,110],"the":[26,47,106,118],"price.":[29],"For":[30],"SNLSTM":[31,56,72,88,107],"(N}=":[32],"1000)":[33,38],"and":[34,46,58,62,67,90,99,115],"(N=":[37],"this":[39],"algorithm":[40,57,61],"calculated":[41],"by":[42],"2":[44],"groups":[45],"total":[48],"samples":[49],"are":[50,92],"2000":[51],"g-power":[53],"0.8,":[54],"both":[55,65],"also":[63,116],"for":[64],"algorithms":[66],"is":[69,108],"working.":[70],"The":[71],"(63.10%)":[73],"has":[74],"a":[75],"better":[76,109],"rate":[78],"compared":[79],"(61.03%).":[83],"Statistical":[84],"Significance":[85],"differences":[86],"between":[87],"Algorithm":[89],"Backpropagation":[91],"considered":[93],"be":[95],"$(\\mathrm{p}\\lt0.05)$":[96],"i.e.":[97],"p=.000":[98],"evidence":[100],"as":[101],"statistically":[102],"significant.":[103],"This":[104],"shows":[105],"predicting":[111],"price":[114],"improves":[117],"level":[120],"percentage":[121],"than":[122],"Propagation.":[124]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2025-12-24T23:09:58.560324","created_date":"2025-10-10T00:00:00"}