{"id":"https://openalex.org/W3116000233","doi":"https://doi.org/10.1109/wcsp49889.2020.9299775","title":"A Novel Density-Based Performance Evaluation Index for Multipath Components Clustering","display_name":"A Novel Density-Based Performance Evaluation Index for Multipath Components Clustering","publication_year":2020,"publication_date":"2020-10-21","ids":{"openalex":"https://openalex.org/W3116000233","doi":"https://doi.org/10.1109/wcsp49889.2020.9299775","mag":"3116000233"},"language":"en","primary_location":{"id":"doi:10.1109/wcsp49889.2020.9299775","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wcsp49889.2020.9299775","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Conference on Wireless Communications and Signal Processing (WCSP)","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/A5090482974","display_name":"Yuanyuan Qiao","orcid":"https://orcid.org/0000-0002-3573-9847"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanyuan Qiao","raw_affiliation_strings":["Institute of Broadband Wireless Mobile Communications, Beijing Jiaotong University, Beijing, P.R.China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Broadband Wireless Mobile Communications, Beijing Jiaotong University, Beijing, P.R.China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002476927","display_name":"Zhichao Yang","orcid":"https://orcid.org/0000-0002-2797-4257"},"institutions":[{"id":"https://openalex.org/I153473198","display_name":"North China Electric Power University","ror":"https://ror.org/04qr5t414","country_code":"CN","type":"education","lineage":["https://openalex.org/I153473198"]},{"id":"https://openalex.org/I4392738113","display_name":"China Electric Power Research Institute","ror":"https://ror.org/05ehpzy81","country_code":null,"type":"facility","lineage":["https://openalex.org/I17442442","https://openalex.org/I4392738113"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhichao Yang","raw_affiliation_strings":["China Electric Power Research Institute, Beijing, P.R.China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Electric Power Research Institute, Beijing, P.R.China","institution_ids":["https://openalex.org/I153473198","https://openalex.org/I4392738113"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087504521","display_name":"Tao Zhou","orcid":"https://orcid.org/0000-0001-9908-255X"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Zhou","raw_affiliation_strings":["Institute of Broadband Wireless Mobile Communications, Beijing Jiaotong University, Beijing, P.R.China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Broadband Wireless Mobile Communications, Beijing Jiaotong University, Beijing, P.R.China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110464721","display_name":"Shanshan Lin","orcid":null},"institutions":[{"id":"https://openalex.org/I153473198","display_name":"North China Electric Power University","ror":"https://ror.org/04qr5t414","country_code":"CN","type":"education","lineage":["https://openalex.org/I153473198"]},{"id":"https://openalex.org/I4392738113","display_name":"China Electric Power Research Institute","ror":"https://ror.org/05ehpzy81","country_code":null,"type":"facility","lineage":["https://openalex.org/I17442442","https://openalex.org/I4392738113"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shanshan Lin","raw_affiliation_strings":["China Electric Power Research Institute, Beijing, P.R.China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Electric Power Research Institute, Beijing, P.R.China","institution_ids":["https://openalex.org/I153473198","https://openalex.org/I4392738113"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041358701","display_name":"Daohua Zhu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Daohua Zhu","raw_affiliation_strings":["State Grid Jiangsu Electric Power Co., Ltd., Electric Power Research Institute, Nanjing, P.R.China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Grid Jiangsu Electric Power Co., Ltd., Electric Power Research Institute, Nanjing, P.R.China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2708,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.66287608,"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":"499","last_page":"503"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9994999766349792,"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9994999766349792,"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"}},{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9977999925613403,"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"}},{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.979200005531311,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.8316503763198853},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.8312455415725708},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6483404636383057},{"id":"https://openalex.org/keywords/expectation\u2013maximization-algorithm","display_name":"Expectation\u2013maximization algorithm","score":0.5536577701568604},{"id":"https://openalex.org/keywords/index","display_name":"Index (typography)","score":0.4992091655731201},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4955817461013794},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.43126416206359863},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.428881973028183},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4270492494106293},{"id":"https://openalex.org/keywords/cluster","display_name":"Cluster (spacecraft)","score":0.4147009253501892},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.41443127393722534},{"id":"https://openalex.org/keywords/maximization","display_name":"Maximization","score":0.4122897982597351},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3470584750175476},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.26691675186157227},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.17036882042884827},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.15209877490997314},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.12960019707679749}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.8316503763198853},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.8312455415725708},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6483404636383057},{"id":"https://openalex.org/C182081679","wikidata":"https://www.wikidata.org/wiki/Q1275153","display_name":"Expectation\u2013maximization algorithm","level":3,"score":0.5536577701568604},{"id":"https://openalex.org/C2777382242","wikidata":"https://www.wikidata.org/wiki/Q6017816","display_name":"Index (typography)","level":2,"score":0.4992091655731201},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4955817461013794},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.43126416206359863},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.428881973028183},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4270492494106293},{"id":"https://openalex.org/C164866538","wikidata":"https://www.wikidata.org/wiki/Q367351","display_name":"Cluster (spacecraft)","level":2,"score":0.4147009253501892},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.41443127393722534},{"id":"https://openalex.org/C2776330181","wikidata":"https://www.wikidata.org/wiki/Q18358244","display_name":"Maximization","level":2,"score":0.4122897982597351},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3470584750175476},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.26691675186157227},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.17036882042884827},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.15209877490997314},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.12960019707679749},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/wcsp49889.2020.9299775","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wcsp49889.2020.9299775","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Conference on Wireless Communications and Signal Processing (WCSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320326707","display_name":"State Grid Corporation of China","ror":"https://ror.org/05twwhs70"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W61015563","https://openalex.org/W1697154133","https://openalex.org/W1922250139","https://openalex.org/W1929192797","https://openalex.org/W1987971958","https://openalex.org/W2020195251","https://openalex.org/W2025299767","https://openalex.org/W2051224630","https://openalex.org/W2085487226","https://openalex.org/W2099943676","https://openalex.org/W2113586398","https://openalex.org/W2129066856","https://openalex.org/W2162131626","https://openalex.org/W2171911691","https://openalex.org/W2600156789","https://openalex.org/W2805005199","https://openalex.org/W2948169568","https://openalex.org/W3033789406","https://openalex.org/W6602473807","https://openalex.org/W6640271039","https://openalex.org/W6674840440"],"related_works":["https://openalex.org/W2473373438","https://openalex.org/W2368486525","https://openalex.org/W2077224612","https://openalex.org/W2153481672","https://openalex.org/W2153238387","https://openalex.org/W84255947","https://openalex.org/W4312864369","https://openalex.org/W2014842417","https://openalex.org/W2891133681","https://openalex.org/W2061347451"],"abstract_inverted_index":{"The":[0,43,79,133],"machine":[1,90],"learning":[2,91],"algorithms":[3,152],"applied":[4,72],"in":[5,153],"multipath":[6],"components":[7],"(MPCs)":[8],"clustering":[9,28],"should":[10],"be":[11,71],"evaluated":[12],"by":[13,52,122],"an":[14],"appropriate":[15],"performance":[16,23,87],"index.":[17],"In":[18,112],"this":[19],"paper,":[20],"a":[21,104],"novel":[22],"evaluation":[24,134],"index":[25,45,51,81,119],"for":[26],"MPCs":[27,74,125,154],"is":[29,32,82,120],"proposed,":[30],"which":[31,69,102],"based":[33],"on":[34],"the":[35,47,56,62,86,114,117,123,138,145],"density":[36,58],"of":[37,40,88,116],"clusters":[38],"instead":[39],"cluster":[41],"distance.":[42],"proposed":[44,80,118],"improves":[46],"traditional":[48,110],"S_Dbw":[49],"validity":[50],"taking":[53],"into":[54],"account":[55],"intra-cluster":[57],"obtained":[59],"according":[60],"to":[61,73,84],"Graham":[63],"scanning":[64],"method":[65],"and":[66,96,130,147],"Green's":[67],"formula,":[68],"can":[70],"with":[75],"arbitrary":[76],"distribution":[77],"characteristics.":[78],"used":[83],"evaluate":[85],"different":[89],"algorithms,":[92,101],"such":[93],"as":[94],"K-means":[95,146],"Gaussian":[97],"mixture":[98],"model":[99],"(GMM)":[100],"shows":[103,136],"more":[105],"accurate":[106],"result":[107,135],"than":[108],"other":[109],"indexes.":[111],"addition,":[113],"utility":[115],"verified":[121],"measured":[124],"data":[126],"involving":[127],"both":[128],"delay":[129],"angle":[131],"information.":[132],"that":[137],"variational":[139],"Bayesian":[140],"GMM":[141,150],"(VB-GMM)":[142],"algorithm":[143],"outperforms":[144],"expectation":[148],"maximization":[149],"(EM-GMM)":[151],"clustering.":[155]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
