{"id":"https://openalex.org/W2969534742","doi":"https://doi.org/10.1109/access.2019.2937098","title":"Multi-Step Data Prediction in Wireless Sensor Networks Based on One-Dimensional CNN and Bidirectional LSTM","display_name":"Multi-Step Data Prediction in Wireless Sensor Networks Based on One-Dimensional CNN and Bidirectional LSTM","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2969534742","doi":"https://doi.org/10.1109/access.2019.2937098","mag":"2969534742"},"language":"en","primary_location":{"id":"doi:10.1109/access.2019.2937098","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2937098","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2019.2937098","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5036420194","display_name":"Hongju Cheng","orcid":"https://orcid.org/0000-0002-0768-7859"},"institutions":[{"id":"https://openalex.org/I1327237609","display_name":"Ministry of Education of the People's Republic of China","ror":"https://ror.org/01mv9t934","country_code":"CN","type":"government","lineage":["https://openalex.org/I1327237609","https://openalex.org/I4210127390"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongju Cheng","raw_affiliation_strings":["Key Laboratory of Spatial Data Mining and Information Sharing, Ministry of Education, Fuzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-0768-7859","affiliations":[{"raw_affiliation_string":"Key Laboratory of Spatial Data Mining and Information Sharing, Ministry of Education, Fuzhou, China","institution_ids":["https://openalex.org/I1327237609"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102871595","display_name":"Zhe Xie","orcid":"https://orcid.org/0000-0001-9749-2539"},"institutions":[{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhe Xie","raw_affiliation_strings":["College of Mathematics and Computer Science, Fuzhou University, Fuzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Mathematics and Computer Science, Fuzhou University, Fuzhou, China","institution_ids":["https://openalex.org/I80947539"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046362293","display_name":"Yushi Shi","orcid":"https://orcid.org/0000-0002-1160-6521"},"institutions":[{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yushi Shi","raw_affiliation_strings":["College of Mathematics and Computer Science, Fuzhou University, Fuzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Mathematics and Computer Science, Fuzhou University, Fuzhou, China","institution_ids":["https://openalex.org/I80947539"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103216531","display_name":"Naixue Xiong","orcid":"https://orcid.org/0000-0002-0394-4635"},"institutions":[{"id":"https://openalex.org/I192664086","display_name":"Northeastern State University","ror":"https://ror.org/01z7kzb45","country_code":"US","type":"education","lineage":["https://openalex.org/I192664086"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Naixue Xiong","raw_affiliation_strings":["Department of Mathematics and Computer Science, Northeastern State University, Tahlequah, OK, USA"],"raw_orcid":"https://orcid.org/0000-0002-0394-4635","affiliations":[{"raw_affiliation_string":"Department of Mathematics and Computer Science, Northeastern State University, Tahlequah, OK, USA","institution_ids":["https://openalex.org/I192664086"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":9.5283,"has_fulltext":false,"cited_by_count":133,"citation_normalized_percentile":{"value":0.9817453,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"7","issue":null,"first_page":"117883","last_page":"117896"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10080","display_name":"Energy Efficient Wireless Sensor Networks","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10080","display_name":"Energy Efficient Wireless Sensor Networks","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T12120","display_name":"Air Quality Monitoring and Forecasting","score":0.9937999844551086,"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"}},{"id":"https://openalex.org/T12597","display_name":"Fire Detection and Safety Systems","score":0.9805999994277954,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8456912040710449},{"id":"https://openalex.org/keywords/wireless-sensor-network","display_name":"Wireless sensor network","score":0.8138455748558044},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5296696424484253},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5256487131118774},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.46731990575790405},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.45571163296699524},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.4481585621833801},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.4368040859699249},{"id":"https://openalex.org/keywords/spatial-correlation","display_name":"Spatial correlation","score":0.43651342391967773},{"id":"https://openalex.org/keywords/wireless-network","display_name":"Wireless network","score":0.43122488260269165},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.42299219965934753},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3864748775959015},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.38360321521759033},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.11307284235954285},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.07048231363296509}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8456912040710449},{"id":"https://openalex.org/C24590314","wikidata":"https://www.wikidata.org/wiki/Q336038","display_name":"Wireless sensor network","level":2,"score":0.8138455748558044},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5296696424484253},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5256487131118774},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.46731990575790405},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.45571163296699524},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.4481585621833801},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.4368040859699249},{"id":"https://openalex.org/C150060386","wikidata":"https://www.wikidata.org/wiki/Q7574054","display_name":"Spatial correlation","level":2,"score":0.43651342391967773},{"id":"https://openalex.org/C108037233","wikidata":"https://www.wikidata.org/wiki/Q11375","display_name":"Wireless network","level":3,"score":0.43122488260269165},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.42299219965934753},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3864748775959015},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38360321521759033},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.11307284235954285},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.07048231363296509},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2019.2937098","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2937098","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:1da78f70a25e4fe5bc7e98df786c6de1","is_oa":true,"landing_page_url":"https://doaj.org/article/1da78f70a25e4fe5bc7e98df786c6de1","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 7, Pp 117883-117896 (2019)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2019.2937098","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2937098","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.7400000095367432}],"awards":[{"id":"https://openalex.org/G1944050839","display_name":null,"funder_award_id":"2019J01245","funder_id":"https://openalex.org/F4320321878","funder_display_name":"Natural Science Foundation of Fujian Province"},{"id":"https://openalex.org/G5404143815","display_name":"\u9762\u5411\u670d\u52a1\u7684\u65e0\u7ebf\u4f20\u611f\u5668\u7f51\u7edc\u5173\u8054\u611f\u77e5\u7b56\u7565\u4e0e\u5bb9\u9519\u534f\u540c\u673a\u5236\u7814\u7a76","funder_award_id":"61370210","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321878","display_name":"Natural Science Foundation of Fujian Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1561046637","https://openalex.org/W1989218206","https://openalex.org/W2065252721","https://openalex.org/W2170239483","https://openalex.org/W2274880506","https://openalex.org/W2294756172","https://openalex.org/W2474890436","https://openalex.org/W2541877794","https://openalex.org/W2562640384","https://openalex.org/W2592807177","https://openalex.org/W2765327702","https://openalex.org/W2767577230","https://openalex.org/W2792326773","https://openalex.org/W2794313230","https://openalex.org/W2795803205","https://openalex.org/W2799541071","https://openalex.org/W2800726910","https://openalex.org/W2802249969","https://openalex.org/W2890672150","https://openalex.org/W2898136110","https://openalex.org/W2901841903","https://openalex.org/W2962691244","https://openalex.org/W3105158720","https://openalex.org/W3124189689","https://openalex.org/W6633660258"],"related_works":["https://openalex.org/W4225394202","https://openalex.org/W4298287631","https://openalex.org/W2953061907","https://openalex.org/W1847088711","https://openalex.org/W3036642985","https://openalex.org/W3032952384","https://openalex.org/W3017902212","https://openalex.org/W2964335273","https://openalex.org/W1993382516","https://openalex.org/W2157145317"],"abstract_inverted_index":{"The":[0,65],"increase":[1,33],"of":[2,78,136,168],"network":[3,30,35],"size":[4],"and":[5,32,86,124,128,164,198,203],"sensory":[6,45,102,142,201],"data":[7,41,56,103,163],"leads":[8,88],"to":[9,13,19,28,53,63,89,131,150],"many":[10],"serious":[11],"problems":[12],"the":[14,20,34,44,79,112,133,140,155,165,169,184,189],"wireless":[15,70,83,106],"sensor":[16,60,71,84,107],"networks":[17,72,115],"due":[18],"limited":[21],"energy.":[22],"Data":[23,47],"prediction":[24,48,67,91,104,157,166],"method":[25],"is":[26,158,187,206],"helpful":[27],"reduce":[29],"traffic":[31],"lifetime":[36],"accordingly,":[37],"especially":[38],"by":[39,160],"exploring":[40],"correlation":[42,81,186],"among":[43],"data.":[46,143],"can":[49,194],"also":[50],"be":[51],"used":[52,149],"recover":[54],"abnormal/lost":[55],"in":[57,69,105,182],"case":[58],"these":[59,145],"nodes":[61],"fail":[62],"work.":[64],"current":[66],"methods":[68],"do":[73],"not":[74],"make":[75],"full":[76],"usage":[77],"spatial-temporal":[80,185],"between":[82],"nodes,":[85],"thus":[87],"higher":[90],"error":[92],"relatively.":[93],"This":[94],"paper":[95],"proposes":[96],"a":[97],"novel":[98],"model":[99,193],"for":[100],"multi-step":[101,156,191,196],"network.":[108],"Firstly,":[109],"we":[110],"introduce":[111],"artificial":[113],"neural":[114],"based":[116],"on":[117],"1-D":[118],"CNN":[119],"(One-Dimensional":[120],"Convolutional":[121],"Neural":[122],"Network)":[123],"Bi-LSTM":[125],"(Bidirectional":[126],"Long":[127],"Short-Term":[129],"Memory)":[130],"get":[132],"abstract":[134,146],"features":[135,147],"different":[137],"attributes":[138],"via":[139],"pre-processed":[141],"Then,":[144],"are":[148],"obtain":[151],"one-step":[152],"prediction.":[153],"Finally,":[154],"introduced":[159],"using":[161],"historical":[162],"results":[167,174],"previous":[170],"step":[171],"iteratively.":[172],"Experiment":[173],"show":[175],"that":[176],"after":[177],"selecting":[178],"suitable":[179],"node":[180],"combinations":[181],"which":[183],"highlighted,":[188],"proposed":[190],"predictive":[192],"predict":[195],"(short":[197],"medium":[199],"term)":[200],"data,":[202],"its":[204],"performance":[205],"better":[207],"compared":[208],"with":[209],"other":[210],"related":[211],"methods.":[212]},"counts_by_year":[{"year":2026,"cited_by_count":7},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":12},{"year":2023,"cited_by_count":42},{"year":2022,"cited_by_count":27},{"year":2021,"cited_by_count":12},{"year":2020,"cited_by_count":21},{"year":2019,"cited_by_count":1}],"updated_date":"2026-08-11T07:18:39.950985","created_date":"2025-10-10T00:00:00"}