{"id":"https://openalex.org/W3213649367","doi":"https://doi.org/10.1155/2021/2943678","title":"Prediction Method of College Students\u2019 Psychological Pressure Based on Deep Neural Network","display_name":"Prediction Method of College Students\u2019 Psychological Pressure Based on Deep Neural Network","publication_year":2021,"publication_date":"2021-11-12","ids":{"openalex":"https://openalex.org/W3213649367","doi":"https://doi.org/10.1155/2021/2943678","mag":"3213649367"},"language":"en","primary_location":{"id":"doi:10.1155/2021/2943678","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2021/2943678","pdf_url":"https://downloads.hindawi.com/journals/sp/2021/2943678.pdf","source":{"id":"https://openalex.org/S166774750","display_name":"Scientific Programming","issn_l":"1058-9244","issn":["1058-9244","1875-919X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Scientific Programming","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://downloads.hindawi.com/journals/sp/2021/2943678.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100716795","display_name":"Bing Wang","orcid":"https://orcid.org/0000-0002-5880-6141"},"institutions":[{"id":"https://openalex.org/I47689461","display_name":"Northeast Forestry University","ror":"https://ror.org/02yxnh564","country_code":"CN","type":"education","lineage":["https://openalex.org/I47689461"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bing Wang","raw_affiliation_strings":["School of Traffic and Transportation, Northeast Forestry University, Haerbin 150000, China"],"affiliations":[{"raw_affiliation_string":"School of Traffic and Transportation, Northeast Forestry University, Haerbin 150000, China","institution_ids":["https://openalex.org/I47689461"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100763657","display_name":"Sitong Liu","orcid":"https://orcid.org/0000-0001-7355-1549"},"institutions":[{"id":"https://openalex.org/I47689461","display_name":"Northeast Forestry University","ror":"https://ror.org/02yxnh564","country_code":"CN","type":"education","lineage":["https://openalex.org/I47689461"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Sitong Liu","raw_affiliation_strings":["School of Traffic and Transportation, Northeast Forestry University, Haerbin 150000, China"],"affiliations":[{"raw_affiliation_string":"School of Traffic and Transportation, Northeast Forestry University, Haerbin 150000, China","institution_ids":["https://openalex.org/I47689461"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100763657"],"corresponding_institution_ids":["https://openalex.org/I47689461"],"apc_list":{"value":1800,"currency":"USD","value_usd":1800},"apc_paid":{"value":1800,"currency":"USD","value_usd":1800},"fwci":0.4079,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.69679264,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"2021","issue":null,"first_page":"1","last_page":"9"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14413","display_name":"Advanced Technologies in Various Fields","score":0.9327999949455261,"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/T14413","display_name":"Advanced Technologies in Various Fields","score":0.9327999949455261,"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/artificial-neural-network","display_name":"Artificial neural network","score":0.788602888584137},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.556864857673645},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.49000754952430725},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.4627867043018341},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4166751801967621},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.39318203926086426},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.39291107654571533}],"concepts":[{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.788602888584137},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.556864857673645},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.49000754952430725},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.4627867043018341},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4166751801967621},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39318203926086426},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.39291107654571533},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1155/2021/2943678","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2021/2943678","pdf_url":"https://downloads.hindawi.com/journals/sp/2021/2943678.pdf","source":{"id":"https://openalex.org/S166774750","display_name":"Scientific Programming","issn_l":"1058-9244","issn":["1058-9244","1875-919X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Scientific Programming","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:671b7863c1f846e481afa47d650efc83","is_oa":true,"landing_page_url":"https://doaj.org/article/671b7863c1f846e481afa47d650efc83","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Scientific Programming, Vol 2021 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1155/2021/2943678","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2021/2943678","pdf_url":"https://downloads.hindawi.com/journals/sp/2021/2943678.pdf","source":{"id":"https://openalex.org/S166774750","display_name":"Scientific Programming","issn_l":"1058-9244","issn":["1058-9244","1875-919X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Scientific Programming","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.4300000071525574,"id":"https://metadata.un.org/sdg/1","display_name":"No poverty"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3213649367.pdf","grobid_xml":"https://content.openalex.org/works/W3213649367.grobid-xml"},"referenced_works_count":40,"referenced_works":["https://openalex.org/W2764058170","https://openalex.org/W2805850559","https://openalex.org/W2893372022","https://openalex.org/W2908606342","https://openalex.org/W2921081738","https://openalex.org/W2933916181","https://openalex.org/W2940789762","https://openalex.org/W2945242294","https://openalex.org/W2952898185","https://openalex.org/W2963418397","https://openalex.org/W2982375756","https://openalex.org/W2989857117","https://openalex.org/W2991526369","https://openalex.org/W2994763368","https://openalex.org/W2996549886","https://openalex.org/W2996927594","https://openalex.org/W3005359536","https://openalex.org/W3020634318","https://openalex.org/W3033763369","https://openalex.org/W3036321681","https://openalex.org/W3040176325","https://openalex.org/W3047986505","https://openalex.org/W3094483422","https://openalex.org/W3094920651","https://openalex.org/W3095349462","https://openalex.org/W3098448153","https://openalex.org/W3102087799","https://openalex.org/W3104190385","https://openalex.org/W3113162324","https://openalex.org/W3128999341","https://openalex.org/W3129500469","https://openalex.org/W3129811851","https://openalex.org/W3144057295","https://openalex.org/W3159031898","https://openalex.org/W3163734136","https://openalex.org/W3167031531","https://openalex.org/W3167210698","https://openalex.org/W3167841307","https://openalex.org/W3173765301","https://openalex.org/W3182844055"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W4313488044","https://openalex.org/W3209574120","https://openalex.org/W4312192474","https://openalex.org/W4210805261"],"abstract_inverted_index":{"Aiming":[0],"at":[1],"the":[2,15,51,58,70,79,95,101,113,116,130,145],"problems":[3],"of":[4,40,62,84,104,112,118,149],"low":[5],"prediction":[6,12,19,24,67,75,117],"accuracy":[7,146],"and":[8,10,38,44,68,141,147],"efficiency":[9,148],"poor":[11],"effect":[13],"in":[14,109,135],"current":[16],"psychological":[17,22,65,73,107,121,139,152],"pressure":[18,23,66,74,108,122,140,153],"methods,":[20],"a":[21],"method":[25,132],"for":[26],"college":[27,63,71,105,119,137,150],"students":[28],"based":[29],"on":[30],"deep":[31,52,80],"neural":[32,42,53,81],"network":[33,43,82,89],"is":[34,92,123,133],"proposed.":[35],"The":[36,87,125],"structure":[37],"algorithm":[39,83],"depth":[41],"gray":[45,85],"theory":[46],"model":[47,76,91],"are":[48],"analyzed.":[49],"Using":[50],"network,":[54,115],"this":[55],"paper":[56],"establishes":[57],"sample":[59],"set":[60],"data":[61],"students\u2019":[64,72,106,120,138,151],"constructs":[69],"combined":[77],"with":[78],"theory.":[86],"physical":[88,114],"information":[90],"formed":[93],"through":[94],"relationship":[96],"between":[97],"neurons.":[98],"According":[99],"to":[100],"dynamic":[102],"changes":[103],"each":[110],"neuron":[111],"completed.":[124],"experimental":[126],"results":[127],"show":[128],"that":[129],"proposed":[131],"effective":[134],"predicting":[136],"can":[142],"effectively":[143],"improve":[144],"prediction.":[154]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
