{"id":"https://openalex.org/W4365800537","doi":"https://doi.org/10.1145/3582084.3582089","title":"Node Localization in Range-Free 3D-WSNs Using New DV-Hop Algorithm Based Machine Learning Techniques","display_name":"Node Localization in Range-Free 3D-WSNs Using New DV-Hop Algorithm Based Machine Learning Techniques","publication_year":2022,"publication_date":"2022-11-25","ids":{"openalex":"https://openalex.org/W4365800537","doi":"https://doi.org/10.1145/3582084.3582089"},"language":"en","primary_location":{"id":"doi:10.1145/3582084.3582089","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3582084.3582089","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 4th International Conference on Software Engineering and Development","raw_type":"proceedings-article"},"type":"conference-paper","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/A5075747378","display_name":"Oumaima Liouane","orcid":"https://orcid.org/0000-0001-7135-4867"},"institutions":[{"id":"https://openalex.org/I166928557","display_name":"University of Monastir","ror":"https://ror.org/00nhtcg76","country_code":"TN","type":"education","lineage":["https://openalex.org/I166928557"]},{"id":"https://openalex.org/I4391012590","display_name":"Ecole Nationale d'Ing\u00e9nieurs de Monastir","ror":"https://ror.org/045yr8682","country_code":null,"type":"education","lineage":["https://openalex.org/I166928557","https://openalex.org/I4391012590"]}],"countries":["TN"],"is_corresponding":false,"raw_author_name":"Oumaima Liouane","raw_affiliation_strings":["University of Monastir, National Engineering School of Monastir, Tunisia"],"raw_orcid":"https://orcid.org/0000-0001-7135-4867","affiliations":[{"raw_affiliation_string":"University of Monastir, National Engineering School of Monastir, Tunisia","institution_ids":["https://openalex.org/I166928557","https://openalex.org/I4391012590"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013614226","display_name":"Smain Femmam","orcid":"https://orcid.org/0000-0001-5366-0481"},"institutions":[{"id":"https://openalex.org/I2800745255","display_name":"Universit\u00e9 de Haute-Alsace","ror":"https://ror.org/04k8k6n84","country_code":"FR","type":"education","lineage":["https://openalex.org/I2800745255"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Smain Femmam","raw_affiliation_strings":["Department of Networks and Communications, Haute-Alsace University, France"],"raw_orcid":"https://orcid.org/0000-0001-5366-0481","affiliations":[{"raw_affiliation_string":"Department of Networks and Communications, Haute-Alsace University, France","institution_ids":["https://openalex.org/I2800745255"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001627597","display_name":"Toufik Bakir","orcid":"https://orcid.org/0000-0002-3591-8458"},"institutions":[{"id":"https://openalex.org/I177064439","display_name":"Universit\u00e9 de Bourgogne","ror":"https://ror.org/03k1bsr36","country_code":"FR","type":"education","lineage":["https://openalex.org/I177064439"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Toufik Bakir","raw_affiliation_strings":["Bourgogne University, France"],"raw_orcid":"https://orcid.org/0000-0002-3591-8458","affiliations":[{"raw_affiliation_string":"Bourgogne University, France","institution_ids":["https://openalex.org/I177064439"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002102526","display_name":"Abdessalem Ben Abdelali","orcid":"https://orcid.org/0000-0002-3218-1964"},"institutions":[{"id":"https://openalex.org/I166928557","display_name":"University of Monastir","ror":"https://ror.org/00nhtcg76","country_code":"TN","type":"education","lineage":["https://openalex.org/I166928557"]}],"countries":["TN"],"is_corresponding":false,"raw_author_name":"Abdessalem Ben Abdelali","raw_affiliation_strings":["University of Monastir, ISIMM of Monastirr, Tunisia"],"raw_orcid":"https://orcid.org/0000-0002-3218-1964","affiliations":[{"raw_affiliation_string":"University of Monastir, ISIMM of Monastirr, Tunisia","institution_ids":["https://openalex.org/I166928557"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.826,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.71550388,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"21","last_page":"25"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10080","display_name":"Energy Efficient Wireless Sensor Networks","score":0.9976999759674072,"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/T11192","display_name":"Underwater Vehicles and Communication Systems","score":0.9954000115394592,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"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":0.7474771738052368},{"id":"https://openalex.org/keywords/wireless-sensor-network","display_name":"Wireless sensor network","score":0.7137500643730164},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6813995242118835},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.6281439065933228},{"id":"https://openalex.org/keywords/extreme-learning-machine","display_name":"Extreme learning machine","score":0.5164187550544739},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5132796764373779},{"id":"https://openalex.org/keywords/hop","display_name":"Hop (telecommunications)","score":0.5037171244621277},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.4704664647579193},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4083336889743805},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3770257830619812},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.19611045718193054},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.10448122024536133}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7474771738052368},{"id":"https://openalex.org/C24590314","wikidata":"https://www.wikidata.org/wiki/Q336038","display_name":"Wireless sensor network","level":2,"score":0.7137500643730164},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6813995242118835},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.6281439065933228},{"id":"https://openalex.org/C2780150128","wikidata":"https://www.wikidata.org/wiki/Q21948731","display_name":"Extreme learning machine","level":3,"score":0.5164187550544739},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5132796764373779},{"id":"https://openalex.org/C25906391","wikidata":"https://www.wikidata.org/wiki/Q1432381","display_name":"Hop (telecommunications)","level":2,"score":0.5037171244621277},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.4704664647579193},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4083336889743805},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3770257830619812},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.19611045718193054},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.10448122024536133},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"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":1,"locations":[{"id":"doi:10.1145/3582084.3582089","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3582084.3582089","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 4th International Conference on Software Engineering and Development","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":19,"referenced_works":["https://openalex.org/W2042046050","https://openalex.org/W2052978627","https://openalex.org/W2125150720","https://openalex.org/W2166237942","https://openalex.org/W2772188068","https://openalex.org/W2793763890","https://openalex.org/W2799470827","https://openalex.org/W2921023389","https://openalex.org/W2946177678","https://openalex.org/W3045276361","https://openalex.org/W3109636545","https://openalex.org/W3115102658","https://openalex.org/W3175810642","https://openalex.org/W3217313657","https://openalex.org/W4200210047","https://openalex.org/W4200234907","https://openalex.org/W4237533281","https://openalex.org/W6600822972","https://openalex.org/W6648582430"],"related_works":["https://openalex.org/W2067443264","https://openalex.org/W31566076","https://openalex.org/W4297902562","https://openalex.org/W2741186499","https://openalex.org/W2804652951","https://openalex.org/W2556335056","https://openalex.org/W2002678693","https://openalex.org/W1584764049","https://openalex.org/W2743832667","https://openalex.org/W4386889652"],"abstract_inverted_index":{"In":[0,27,116],"many":[1,100],"Wireless":[2],"Sensor":[3],"Network":[4],"(WSN)":[5],"applications,":[6],"location":[7,251],"is":[8,17,106,136,152,210],"critical.":[9],"Another":[10],"intriguing":[11],"aspect":[12],"of":[13,97,123,130,169,183,208,219,245],"the":[14,18,49,57,95,139,184,190,201,217,220,228,241],"acquired":[15],"data":[16],"ability":[19],"to":[20,29,45,56,85,108,149,197,254],"obtain":[21],"exact":[22],"information":[23],"about":[24],"sensors'":[25],"locations.":[26],"order":[28],"localize":[30],"multi-hop":[31],"WSNs,":[32],"based":[33],"connectivity":[34],"algorithms":[35,112,172],"use":[36],"their":[37],"benefits,":[38],"such":[39],"as":[40],"simplicity":[41],"and":[42,76,227,247],"acceptable":[43],"accuracy,":[44],"do":[46],"so.":[47],"However,":[48],"localization":[50,84,87,151,185,192,203,236,243],"accuracy":[51,96,209,252],"may":[52],"be":[53],"limited":[54],"due":[55],"two-":[58],"or":[59,63],"three-dimensional":[60],"environment":[61],"(2D":[62],"3D).":[64],"Range-Free":[65],"3D-WSNs":[66,239],"can":[67],"benefit":[68],"from":[69],"an":[70,77],"analytic":[71],"model":[72,186],"for":[73,83,113,119,224,232,238],"hop-size":[74,225],"quantization":[75,129,223],"Extreme":[78],"Learning":[79],"Machine":[80],"(ELM)":[81,143],"method":[82,157,163,237],"reduce":[86],"errors.":[88],"The":[89,181],"additional":[90],"third":[91],"dimension":[92],"greatly":[93],"affects":[94],"localization.":[98],"Since":[99],"applications":[101],"require":[102],"3D":[103,114,134],"localization,":[104],"it":[105],"important":[107],"develop":[109],"efficient":[110],"self-localization":[111],"WSNs.":[115],"this":[117],"paper,":[118],"a":[120,126,146,155,161,167,249],"uniform":[121],"distribution":[122],"sensor":[124],"nodes,":[125],"new":[127,147],"probabilistic":[128],"hop":[131,222],"size":[132],"in":[133,178,206],"WSNs":[135],"proposed.":[137],"Moreover,":[138],"extreme":[140],"learning":[141],"machine":[142],"which":[144],"represents":[145],"approach":[148],"WSN":[150],"exploited":[153],"combining":[154],"conventional":[156],"(probabilistic":[158],"approach)":[159],"with":[160],"non-conventional":[162],"(Machine":[164],"Learning).":[165],"For":[166],"variety":[168],"conditions,":[170],"our":[171,235],"have":[173],"been":[174],"tested":[175],"through":[176],"simulation":[177,214],"isotropic":[179],"settings.":[180],"performance":[182,205],"was":[187,230],"assessed":[188],"using":[189],"average":[191,242],"error":[193,244],"(LE).":[194],"When":[195],"compared":[196,253],"previous":[198],"3D-DV-Hop":[199],"heuristics,":[200],"suggested":[202],"algorithm's":[204],"terms":[207],"clearly":[211],"demonstrated":[212],"by":[213],"data.":[215],"With":[216],"help":[218],"predicted":[221],"estimation":[226],"ELM":[229],"used":[231],"position":[233],"estimation,":[234],"lowers":[240],"nodes":[246],"has":[248],"greater":[250],"its":[255],"rivals.":[256]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}