{"id":"https://openalex.org/W4283737541","doi":"https://doi.org/10.3390/s22134967","title":"Comparative Analysis of Major Machine-Learning-Based Path Loss Models for Enclosed Indoor Channels","display_name":"Comparative Analysis of Major Machine-Learning-Based Path Loss Models for Enclosed Indoor Channels","publication_year":2022,"publication_date":"2022-06-30","ids":{"openalex":"https://openalex.org/W4283737541","doi":"https://doi.org/10.3390/s22134967","pmid":"https://pubmed.ncbi.nlm.nih.gov/35808457"},"language":"en","primary_location":{"id":"doi:10.3390/s22134967","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22134967","pdf_url":"https://www.mdpi.com/1424-8220/22/13/4967/pdf?version=1656596003","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/22/13/4967/pdf?version=1656596003","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5057920182","display_name":"Mohamed K. Elmezughi","orcid":"https://orcid.org/0000-0001-8791-0311"},"institutions":[{"id":"https://openalex.org/I95023434","display_name":"University of KwaZulu-Natal","ror":"https://ror.org/04qzfn040","country_code":"ZA","type":"education","lineage":["https://openalex.org/I95023434"]}],"countries":["ZA"],"is_corresponding":true,"raw_author_name":"Mohamed K. Elmezughi","raw_affiliation_strings":["The Discipline of Electrical, Electronic and Computer Engineering, University of KwaZulu-Natal, Durban 4041, South Africa"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Discipline of Electrical, Electronic and Computer Engineering, University of KwaZulu-Natal, Durban 4041, South Africa","institution_ids":["https://openalex.org/I95023434"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047159019","display_name":"Omran Salih","orcid":"https://orcid.org/0000-0002-7861-5502"},"institutions":[{"id":"https://openalex.org/I177181097","display_name":"Durban University of Technology","ror":"https://ror.org/0303y7a51","country_code":"ZA","type":"education","lineage":["https://openalex.org/I177181097"]}],"countries":["ZA"],"is_corresponding":true,"raw_author_name":"Omran Salih","raw_affiliation_strings":["Institute of Systems Science, Durban University of Technology, Durban 4000, South Africa"],"raw_orcid":"https://orcid.org/0000-0002-7861-5502","affiliations":[{"raw_affiliation_string":"Institute of Systems Science, Durban University of Technology, Durban 4000, South Africa","institution_ids":["https://openalex.org/I177181097"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047089710","display_name":"Thomas J. Afullo","orcid":"https://orcid.org/0000-0002-2710-4577"},"institutions":[{"id":"https://openalex.org/I95023434","display_name":"University of KwaZulu-Natal","ror":"https://ror.org/04qzfn040","country_code":"ZA","type":"education","lineage":["https://openalex.org/I95023434"]}],"countries":["ZA"],"is_corresponding":false,"raw_author_name":"Thomas J. Afullo","raw_affiliation_strings":["The Discipline of Electrical, Electronic and Computer Engineering, University of KwaZulu-Natal, Durban 4041, South Africa"],"raw_orcid":"https://orcid.org/0000-0002-2710-4577","affiliations":[{"raw_affiliation_string":"The Discipline of Electrical, Electronic and Computer Engineering, University of KwaZulu-Natal, Durban 4041, South Africa","institution_ids":["https://openalex.org/I95023434"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078039710","display_name":"Kevin J. Duffy","orcid":"https://orcid.org/0000-0002-2580-8984"},"institutions":[{"id":"https://openalex.org/I177181097","display_name":"Durban University of Technology","ror":"https://ror.org/0303y7a51","country_code":"ZA","type":"education","lineage":["https://openalex.org/I177181097"]}],"countries":["ZA"],"is_corresponding":false,"raw_author_name":"Kevin J. Duffy","raw_affiliation_strings":["Institute of Systems Science, Durban University of Technology, Durban 4000, South Africa"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Systems Science, Durban University of Technology, Durban 4000, South Africa","institution_ids":["https://openalex.org/I177181097"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5047159019","https://openalex.org/A5057920182"],"corresponding_institution_ids":["https://openalex.org/I177181097","https://openalex.org/I95023434"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2673},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2673},"fwci":2.6792,"has_fulltext":false,"cited_by_count":42,"citation_normalized_percentile":{"value":0.90847424,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"22","issue":"13","first_page":"4967","last_page":"4967"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10936","display_name":"Millimeter-Wave Propagation and Modeling","score":0.9998000264167786,"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/T10936","display_name":"Millimeter-Wave Propagation and Modeling","score":0.9998000264167786,"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/T12146","display_name":"Power Line Communications and Noise","score":0.9824000000953674,"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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9785000085830688,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/path-loss","display_name":"Path loss","score":0.8130532503128052},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.7397956252098083},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6602253913879395},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6382746696472168},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5905576348304749},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5875768661499023},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.5829091668128967},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5369579195976257},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.4900616407394409},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.48631104826927185},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.4841623902320862},{"id":"https://openalex.org/keywords/wireless-network","display_name":"Wireless network","score":0.47279542684555054},{"id":"https://openalex.org/keywords/linear-regression","display_name":"Linear regression","score":0.43691694736480713},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16652816534042358},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1598704755306244},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.15229332447052002}],"concepts":[{"id":"https://openalex.org/C194273485","wikidata":"https://www.wikidata.org/wiki/Q1478845","display_name":"Path loss","level":3,"score":0.8130532503128052},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.7397956252098083},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6602253913879395},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6382746696472168},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5905576348304749},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5875768661499023},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.5829091668128967},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5369579195976257},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.4900616407394409},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.48631104826927185},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.4841623902320862},{"id":"https://openalex.org/C108037233","wikidata":"https://www.wikidata.org/wiki/Q11375","display_name":"Wireless network","level":3,"score":0.47279542684555054},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.43691694736480713},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16652816534042358},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1598704755306244},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.15229332447052002}],"mesh":[{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005544","descriptor_name":"Forecasting","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005544","descriptor_name":"Forecasting","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005544","descriptor_name":"Forecasting","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016014","descriptor_name":"Linear Models","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016014","descriptor_name":"Linear Models","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016014","descriptor_name":"Linear Models","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":5,"locations":[{"id":"doi:10.3390/s22134967","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22134967","pdf_url":"https://www.mdpi.com/1424-8220/22/13/4967/pdf?version=1656596003","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:35808457","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35808457","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:9269839","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9269839","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors (Basel)","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:146507658b5f4fc0888626d1811330ee","is_oa":true,"landing_page_url":"https://doaj.org/article/146507658b5f4fc0888626d1811330ee","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":"Sensors, Vol 22, Iss 13, p 4967 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/22/13/4967/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/s22134967","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors; Volume 22; Issue 13; Pages: 4967","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/s22134967","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22134967","pdf_url":"https://www.mdpi.com/1424-8220/22/13/4967/pdf?version=1656596003","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4283737541.pdf"},"referenced_works_count":89,"referenced_works":["https://openalex.org/W60686164","https://openalex.org/W1437335841","https://openalex.org/W2016023958","https://openalex.org/W2017537474","https://openalex.org/W2025053102","https://openalex.org/W2041779820","https://openalex.org/W2059210892","https://openalex.org/W2064675550","https://openalex.org/W2096032932","https://openalex.org/W2099878889","https://openalex.org/W2107878631","https://openalex.org/W2116334496","https://openalex.org/W2119281476","https://openalex.org/W2122786026","https://openalex.org/W2131241448","https://openalex.org/W2141080987","https://openalex.org/W2143027030","https://openalex.org/W2145576157","https://openalex.org/W2149298154","https://openalex.org/W2169802641","https://openalex.org/W2219770862","https://openalex.org/W2299676078","https://openalex.org/W2530944180","https://openalex.org/W2534482937","https://openalex.org/W2578999646","https://openalex.org/W2584943905","https://openalex.org/W2589086328","https://openalex.org/W2593217710","https://openalex.org/W2616222121","https://openalex.org/W2732547613","https://openalex.org/W2745902057","https://openalex.org/W2751375634","https://openalex.org/W2756179212","https://openalex.org/W2767585020","https://openalex.org/W2781282357","https://openalex.org/W2788671996","https://openalex.org/W2798650501","https://openalex.org/W2803794770","https://openalex.org/W2805882901","https://openalex.org/W2806700348","https://openalex.org/W2807927039","https://openalex.org/W2886855120","https://openalex.org/W2893731701","https://openalex.org/W2907502017","https://openalex.org/W2908884349","https://openalex.org/W2920046745","https://openalex.org/W2926974107","https://openalex.org/W2934397973","https://openalex.org/W2936660115","https://openalex.org/W2937306336","https://openalex.org/W2944604179","https://openalex.org/W2949208758","https://openalex.org/W2949676527","https://openalex.org/W2955707520","https://openalex.org/W2963190722","https://openalex.org/W2963296811","https://openalex.org/W2963820229","https://openalex.org/W2963836746","https://openalex.org/W2968233507","https://openalex.org/W2980016373","https://openalex.org/W2982064046","https://openalex.org/W2982504547","https://openalex.org/W2986489130","https://openalex.org/W2996291210","https://openalex.org/W3000408141","https://openalex.org/W3010289950","https://openalex.org/W3014079666","https://openalex.org/W3015635818","https://openalex.org/W3027865426","https://openalex.org/W3038758042","https://openalex.org/W3044392334","https://openalex.org/W3046498183","https://openalex.org/W3082081550","https://openalex.org/W3088564092","https://openalex.org/W3100008240","https://openalex.org/W3104030016","https://openalex.org/W3110501101","https://openalex.org/W3118299338","https://openalex.org/W3127873574","https://openalex.org/W3129785922","https://openalex.org/W3131052410","https://openalex.org/W3160155847","https://openalex.org/W3170796783","https://openalex.org/W3183937157","https://openalex.org/W3192604765","https://openalex.org/W4236137412","https://openalex.org/W6743957770","https://openalex.org/W6757585881","https://openalex.org/W6774415547"],"related_works":["https://openalex.org/W4225394202","https://openalex.org/W4298287631","https://openalex.org/W2953061907","https://openalex.org/W3032952384","https://openalex.org/W2292972763","https://openalex.org/W3144372491","https://openalex.org/W2964006806","https://openalex.org/W3089761018","https://openalex.org/W3189791978","https://openalex.org/W2575795810"],"abstract_inverted_index":{"Unlimited":[0],"access":[1],"to":[2,32,48,52,69,77,170,226],"information":[3],"and":[4,8,14,25,38,72,97,106,147,200,259,265,280],"data":[5,56,169,247],"sharing":[6],"wherever":[7],"at":[9],"any":[10],"time":[11],"for":[12,43,93,207,215,237,248,283],"anyone":[13],"anything":[15],"is":[16,195,206],"a":[17],"fundamental":[18],"component":[19],"of":[20,59,62,65,74,110,224],"fifth-generation":[21],"(5G)":[22],"wireless":[23,45,75,100,249],"communication":[24,101],"beyond.":[26],"Therefore,":[27],"it":[28],"has":[29],"become":[30],"inevitable":[31],"exploit":[33],"the":[34,60,70,78,94,108,131,172,189,198,204,208,212,216,222,234,238,288],"super-high":[35],"frequency":[36,41,83,290],"(SHF)":[37],"millimeter-wave":[39],"(mmWave)":[40],"bands":[42],"future":[44,99],"networks":[46,145,151],"due":[47,68],"their":[49],"attractive":[50],"ability":[51],"provide":[53,171,257],"extremely":[54],"high":[55],"rates":[57],"because":[58],"availability":[61],"vast":[63],"amounts":[64],"bandwidth.":[66],"However,":[67],"characteristics":[71],"sensitivity":[73],"signals":[76],"propagation":[79],"effects":[80],"in":[81,221,243,251,287],"these":[82,272],"bands,":[84],"more":[85],"accurate":[86,279],"path":[87,176,285],"loss":[88,177,286],"prediction":[89,178],"models":[90,163,235,282],"are":[91,154,164,220],"vital":[92],"planning,":[95],"evaluating,":[96],"optimizing":[98],"networks.":[102],"This":[103],"paper":[104,269],"presents":[105],"evaluates":[107],"performance":[109,194],"several":[111],"well-known":[112],"machine":[113],"learning":[114,218,273],"methods,":[115,202],"including":[116],"multiple":[117],"linear":[118],"regression":[119,122,126],"(MLR),":[120],"polynomial":[121],"(PR),":[123],"support":[124],"vector":[125],"(SVR),":[127],"as":[128,130,278],"well":[129],"methods":[132,274],"using":[133],"decision":[134],"trees":[135],"(DT),":[136],"random":[137],"forests":[138],"(RF),":[139],"K-nearest":[140],"neighbors":[141],"(KNN),":[142],"artificial":[143,148],"neural":[144,150],"(ANN),":[146],"recurrent":[149],"(RNN).":[152],"RNNs":[153],"mainly":[155],"based":[156,166],"on":[157,167],"long":[158],"short-term":[159],"memory":[160],"(LSTM).":[161],"The":[162,180,268],"compared":[165],"measurement":[168,246],"best":[173,190],"fitting":[174,244],"machine-learning-based":[175],"models.":[179],"main":[181],"results":[182],"obtained":[183],"from":[184],"this":[185,230],"study":[186],"show":[187],"that":[188,233,271],"root-mean-square":[191],"error":[192],"(RMSE)":[193],"given":[196,217],"by":[197],"ANN":[199],"RNN-LSTM":[201],"while":[203],"worst":[205],"MLR":[209,239],"method.":[210],"All":[211],"RMSE":[213],"values":[214,261],"techniques":[219],"range":[223],"0.0216":[225],"2.9008":[227],"dB.":[228],"Furthermore,":[229],"work":[231],"shows":[232,270],"(except":[236],"model)":[240],"perform":[241],"excellently":[242],"actual":[245],"communications":[250],"enclosed":[252],"indoor":[253],"environments":[254],"since":[255],"they":[256],"R-squared":[258],"correlation":[260],"higher":[262],"than":[263],"0.91":[264],"0.96,":[266],"respectively.":[267],"could":[275],"be":[276],"used":[277],"stable":[281],"predicting":[284],"mmWave":[289],"regime.":[291]},"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":4}],"updated_date":"2026-08-13T07:04:57.449891","created_date":"2022-07-02T00:00:00"}