{"id":"https://openalex.org/W2524703123","doi":"https://doi.org/10.1109/iwcmc.2016.7577048","title":"Outdoor wave propagation model tuning using Data Mining techniques","display_name":"Outdoor wave propagation model tuning using Data Mining techniques","publication_year":2016,"publication_date":"2016-09-01","ids":{"openalex":"https://openalex.org/W2524703123","doi":"https://doi.org/10.1109/iwcmc.2016.7577048","mag":"2524703123"},"language":"en","primary_location":{"id":"doi:10.1109/iwcmc.2016.7577048","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iwcmc.2016.7577048","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Wireless Communications and Mobile Computing Conference (IWCMC)","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/A5079439315","display_name":"Mohamed Ayadi","orcid":"https://orcid.org/0000-0002-8848-8498"},"institutions":[{"id":"https://openalex.org/I212738717","display_name":"Dwarkadas J. Sanghvi College of Engineering","ror":"https://ror.org/04d4hxn32","country_code":"IN","type":"education","lineage":["https://openalex.org/I212738717"]},{"id":"https://openalex.org/I891191580","display_name":"Aalborg University","ror":"https://ror.org/04m5j1k67","country_code":"DK","type":"education","lineage":["https://openalex.org/I891191580"]}],"countries":["DK","IN"],"is_corresponding":true,"raw_author_name":"M. Ayadi","raw_affiliation_strings":["Antennas, Propagation and Radio Networking, Aalborg University, Aalborg st, Denmark","EXTC D. J. Sanghvi College of Engineering, Mumbai, India"],"affiliations":[{"raw_affiliation_string":"Antennas, Propagation and Radio Networking, Aalborg University, Aalborg st, Denmark","institution_ids":["https://openalex.org/I891191580"]},{"raw_affiliation_string":"EXTC D. J. Sanghvi College of Engineering, Mumbai, India","institution_ids":["https://openalex.org/I212738717"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5079439315"],"corresponding_institution_ids":["https://openalex.org/I212738717","https://openalex.org/I891191580"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.09378182,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"3","issue":null,"first_page":"145","last_page":"149"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10936","display_name":"Millimeter-Wave Propagation and Modeling","score":0.998199999332428,"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":0.998199999332428,"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/T13121","display_name":"Radio Wave Propagation Studies","score":0.9896000027656555,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T11234","display_name":"Precipitation Measurement and Analysis","score":0.9700000286102295,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.729945957660675},{"id":"https://openalex.org/keywords/calibration","display_name":"Calibration","score":0.6704306602478027},{"id":"https://openalex.org/keywords/simplicity","display_name":"Simplicity","score":0.5526201128959656},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5439706444740295},{"id":"https://openalex.org/keywords/work","display_name":"Work (physics)","score":0.47467517852783203},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.46444016695022583},{"id":"https://openalex.org/keywords/backpropagation","display_name":"Backpropagation","score":0.444468230009079},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.43623244762420654},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.41201069951057434},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34723833203315735},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1487707495689392},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1318490207195282},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.0906091034412384}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.729945957660675},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.6704306602478027},{"id":"https://openalex.org/C2776372474","wikidata":"https://www.wikidata.org/wiki/Q508291","display_name":"Simplicity","level":2,"score":0.5526201128959656},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5439706444740295},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.47467517852783203},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.46444016695022583},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.444468230009079},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.43623244762420654},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.41201069951057434},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34723833203315735},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1487707495689392},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1318490207195282},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0906091034412384},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"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/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iwcmc.2016.7577048","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iwcmc.2016.7577048","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Wireless Communications and Mobile Computing Conference (IWCMC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5199999809265137,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W104326263","https://openalex.org/W259338706","https://openalex.org/W1559779124","https://openalex.org/W2062526587","https://openalex.org/W2102666158","https://openalex.org/W2132231561","https://openalex.org/W2140190241","https://openalex.org/W2145417574","https://openalex.org/W2147016173","https://openalex.org/W4210466284","https://openalex.org/W6604250108","https://openalex.org/W6633655409","https://openalex.org/W6680704940","https://openalex.org/W6681648139"],"related_works":["https://openalex.org/W2368019753","https://openalex.org/W2333930193","https://openalex.org/W2737356002","https://openalex.org/W2246241526","https://openalex.org/W4301122218","https://openalex.org/W2374150061","https://openalex.org/W2081340182","https://openalex.org/W2369703001","https://openalex.org/W2372323577","https://openalex.org/W2321432690"],"abstract_inverted_index":{"For":[0],"a":[1,47],"long":[2],"time,":[3],"developing":[4],"empirical":[5],"propagation":[6],"models":[7,123],"have":[8],"been":[9],"an":[10],"area":[11,49],"of":[12,14,27,37,116,121,133],"interest":[13],"scientist":[15],"and":[16,22,50,69,94,158],"researchers":[17],"due":[18],"to":[19,67,80,126,129],"their":[20],"simplicity":[21],"low":[23],"cost":[24],"in":[25,34,84,147,150],"term":[26],"used":[28,87],"resources.":[29],"Their":[30],"major":[31],"drawbacks":[32],"reside":[33],"the":[35,61,85,108,114,131,151],"lack":[36],"accuracy":[38,83,132],"which":[39,89],"can":[40],"be":[41],"improved":[42],"by":[43],"adjusting":[44],"model":[45,56],"for":[46,73,155],"given":[48],"frequency.":[51],"This":[52],"operation":[53],"is":[54,100,111,145],"called":[55],"tuning":[57,74],"or":[58],"calibration.":[59],"In":[60],"present":[62,68],"work":[63,139],"we":[64],"are":[65,90,124],"interested":[66],"compare":[70],"two":[71],"methods":[72],"Standard":[75],"Propagation":[76],"Model":[77],"(SPM)":[78],"parameters":[79],"improve":[81],"its":[82],"most":[86],"bands":[88,154],"900MHz,":[91],"1800MHz,":[92],"2100MHz":[93],"2600MHz":[95],"bands.":[96],"The":[97,119],"first":[98],"method":[99,106],"based":[101,112],"on":[102,113],"multi":[103],"linear":[104],"regression":[105],"while":[107],"second":[109],"one":[110],"use":[115],"neural":[117],"network.":[118],"predictions":[120],"tuned":[122],"compared":[125],"real":[127],"measurements":[128,143],"highlight":[130],"each":[134],"one.":[135],"To":[136],"accomplish":[137],"this":[138],"continuous":[140],"wave":[141],"(CW)":[142],"campaign":[144],"conducted":[146],"Tunis":[148],"City":[149],"four":[152],"cited":[153],"urban,":[156],"suburban":[157],"rural":[159],"environments.":[160]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}