{"id":"https://openalex.org/W4415883324","doi":"https://doi.org/10.1109/jstars.2025.3629148","title":"PSFC-LSTM: A Novel Method for LSTM Prediction of Surface Deformation in High-Speed Railway Based on Clustering of PS Point Metadata Features","display_name":"PSFC-LSTM: A Novel Method for LSTM Prediction of Surface Deformation in High-Speed Railway Based on Clustering of PS Point Metadata Features","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4415883324","doi":"https://doi.org/10.1109/jstars.2025.3629148"},"language":"en","primary_location":{"id":"doi:10.1109/jstars.2025.3629148","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2025.3629148","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"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 Journal of Selected Topics in Applied Earth Observations and Remote Sensing","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/jstars.2025.3629148","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100646173","display_name":"Xuedong Zhang","orcid":"https://orcid.org/0000-0001-6900-338X"},"institutions":[{"id":"https://openalex.org/I62853816","display_name":"Beijing University of Civil Engineering and Architecture","ror":"https://ror.org/02yj0p855","country_code":"CN","type":"education","lineage":["https://openalex.org/I62853816"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xuedong Zhang","raw_affiliation_strings":["School of Geomatics and Urban Spatial Informatics, Beijing University of Civil Engineering and Architecture, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Geomatics and Urban Spatial Informatics, Beijing University of Civil Engineering and Architecture, Beijing, China","institution_ids":["https://openalex.org/I62853816"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yaqi Zhang","orcid":"https://orcid.org/0009-0008-8351-4387"},"institutions":[{"id":"https://openalex.org/I62853816","display_name":"Beijing University of Civil Engineering and Architecture","ror":"https://ror.org/02yj0p855","country_code":"CN","type":"education","lineage":["https://openalex.org/I62853816"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yaqi Zhang","raw_affiliation_strings":["School of Geomatics and Urban Spatial Informatics, Beijing University of Civil Engineering and Architecture, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0008-8351-4387","affiliations":[{"raw_affiliation_string":"School of Geomatics and Urban Spatial Informatics, Beijing University of Civil Engineering and Architecture, Beijing, China","institution_ids":["https://openalex.org/I62853816"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101104683","display_name":"Junming Jiang","orcid":null},"institutions":[{"id":"https://openalex.org/I62853816","display_name":"Beijing University of Civil Engineering and Architecture","ror":"https://ror.org/02yj0p855","country_code":"CN","type":"education","lineage":["https://openalex.org/I62853816"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junming Jiang","raw_affiliation_strings":["School of Geomatics and Urban Spatial Informatics, Beijing University of Civil Engineering and Architecture, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Geomatics and Urban Spatial Informatics, Beijing University of Civil Engineering and Architecture, Beijing, China","institution_ids":["https://openalex.org/I62853816"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112121676","display_name":"Yuyang Pang","orcid":null},"institutions":[{"id":"https://openalex.org/I62853816","display_name":"Beijing University of Civil Engineering and Architecture","ror":"https://ror.org/02yj0p855","country_code":"CN","type":"education","lineage":["https://openalex.org/I62853816"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuyang Pang","raw_affiliation_strings":["School of Geomatics and Urban Spatial Informatics, Beijing University of Civil Engineering and Architecture, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Geomatics and Urban Spatial Informatics, Beijing University of Civil Engineering and Architecture, Beijing, China","institution_ids":["https://openalex.org/I62853816"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100646173"],"corresponding_institution_ids":["https://openalex.org/I62853816"],"apc_list":{"value":1250,"currency":"USD","value_usd":1250},"apc_paid":{"value":1250,"currency":"USD","value_usd":1250},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.40038836,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"18","issue":null,"first_page":"29415","last_page":"29432"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10801","display_name":"Synthetic Aperture Radar (SAR) Applications and Techniques","score":0.8224999904632568,"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"}},"topics":[{"id":"https://openalex.org/T10801","display_name":"Synthetic Aperture Radar (SAR) Applications and Techniques","score":0.8224999904632568,"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/T10842","display_name":"Railway Engineering and Dynamics","score":0.09790000319480896,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical 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/T10644","display_name":"Cryospheric studies and observations","score":0.00570000009611249,"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/cluster-analysis","display_name":"Cluster analysis","score":0.7717000246047974},{"id":"https://openalex.org/keywords/deformation","display_name":"Deformation (meteorology)","score":0.6735000014305115},{"id":"https://openalex.org/keywords/metadata","display_name":"Metadata","score":0.6204000115394592},{"id":"https://openalex.org/keywords/interferometric-synthetic-aperture-radar","display_name":"Interferometric synthetic aperture radar","score":0.5605000257492065},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4577000141143799},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.44200000166893005},{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.4343999922275543},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.3950999975204468}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7717000246047974},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7710999846458435},{"id":"https://openalex.org/C204366326","wikidata":"https://www.wikidata.org/wiki/Q3027650","display_name":"Deformation (meteorology)","level":2,"score":0.6735000014305115},{"id":"https://openalex.org/C93518851","wikidata":"https://www.wikidata.org/wiki/Q180160","display_name":"Metadata","level":2,"score":0.6204000115394592},{"id":"https://openalex.org/C22286887","wikidata":"https://www.wikidata.org/wiki/Q1666056","display_name":"Interferometric synthetic aperture radar","level":3,"score":0.5605000257492065},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4577000141143799},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44780001044273376},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.44200000166893005},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.4343999922275543},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4284000098705292},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.3950999975204468},{"id":"https://openalex.org/C180851071","wikidata":"https://www.wikidata.org/wiki/Q849953","display_name":"Subsidence","level":3,"score":0.3562999963760376},{"id":"https://openalex.org/C136428324","wikidata":"https://www.wikidata.org/wiki/Q838414","display_name":"Deformation monitoring","level":3,"score":0.35510000586509705},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3393999934196472},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.31380000710487366},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.3077999949455261},{"id":"https://openalex.org/C46814834","wikidata":"https://www.wikidata.org/wiki/Q1550770","display_name":"Groundwater-related subsidence","level":4,"score":0.29660001397132874},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.27730000019073486},{"id":"https://openalex.org/C163175372","wikidata":"https://www.wikidata.org/wiki/Q3339222","display_name":"Linear model","level":2,"score":0.2694999873638153},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.2678000032901764},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2632000148296356},{"id":"https://openalex.org/C131109320","wikidata":"https://www.wikidata.org/wiki/Q581012","display_name":"Linear prediction","level":2,"score":0.2556000053882599}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/jstars.2025.3629148","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2025.3629148","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"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 Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:ecac1d25caec4a0e91807543f870db06","is_oa":true,"landing_page_url":"https://doaj.org/article/ecac1d25caec4a0e91807543f870db06","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 Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 18, Pp 29415-29432 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/jstars.2025.3629148","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2025.3629148","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"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 Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"To":[0,161],"meet":[1],"the":[2,37,59,86,93,114,118,122,163,190,194,211,217,220,224,230,237,251,262],"urgent":[3],"demand":[4],"for":[5,189,206,275],"accurate":[6],"deformation":[7,90,119,143,153,187,208,276],"prediction":[8,18,45,60],"in":[9,31,200,210,278],"safe":[10],"operation":[11],"of":[12,23,39,53,62,65,92,193,216,265],"high-speed":[13],"railway(HSR),":[14],"a":[15],"novel":[16],"LSTM":[17,136,245],"method":[19,68,156,222,253],"based":[20],"on":[21],"clustering":[22,115],"PS":[24,54,75,94,148,256],"point":[25,55,76,149,257],"metadata":[26,150],"features":[27,73,151],"(PSFC-LSTM)":[28],"is":[29,125,138],"proposed":[30,164],"this":[32,155],"study,":[33],"aiming":[34],"to":[35,49,140,177,181,243,259],"overcome":[36],"limitation":[38],"traditional":[40],"InSAR":[41],"monitoring":[42,184,277],"time":[43,214],"series":[44],"methods":[46],"that":[47,250],"fail":[48],"make":[50],"full":[51],"use":[52],"information,":[56],"and":[57,98,109,152,185,235,272],"improve":[58],"accuracy":[61,264],"surface":[63,266],"subsidence":[64],"HSR.":[66,284],"The":[67,202],"begins":[69],"by":[70,227,233,240],"extracting":[71],"key":[72],"from":[74,173],"metadata,":[77],"which":[78],"are":[79,96],"subsequently":[80],"clustered":[81],"into":[82,100,128],"three":[83],"groups":[84],"using":[85],"K-Means":[87],"algorithm.":[88],"Concurrently,":[89],"trends":[91],"points":[95],"analyzed":[97],"classified":[99],"four":[101,213],"distinct":[102],"types:":[103],"sinusoidal,":[104],"linear":[105,107,110,279],"increasing,":[106],"stable,":[108],"decreasing.":[111],"By":[112,145],"integrating":[113],"results":[116,203],"with":[117],"trend":[120],"classifications,":[121],"study":[123,218],"area":[124],"systematically":[126],"divided":[127],"12":[129],"sub-regions.":[130],"In":[131],"each":[132],"sub-region,":[133],"an":[134],"independent":[135],"model":[137],"employed":[139],"predict":[141],"cumulative":[142,186,207],"variables.":[144],"incorporating":[146],"both":[147],"trends,":[154],"effectively":[157,254],"enhances":[158],"predictive":[159,263],"accuracy.":[160],"validate":[162],"method,":[165],"we":[166],"utilized":[167],"28":[168],"Sentinel-1":[169],"SAR":[170],"acquisitions":[171],"spanning":[172],"October":[174,178],"17,":[175],"2020,":[176],"24,":[179],"2021,":[180],"conduct":[182],"PS-InSAR":[183],"predictions":[188,209],"Jincheng":[191],"section":[192],"Tai-Jiao":[195],"High-Speed":[196],"Railway":[197],"(Tai-Jiao":[198],"HSR)":[199],"China.":[201],"demonstrate":[204],"that,":[205],"final":[212],"periods":[215],"timeframe,":[219],"PSFC-LSTM":[221,252],"reduced":[223],"average":[225,231,238],"RMSE":[226],"13.8%,":[228],"lowered":[229],"MAE":[232],"26.0%,":[234],"improved":[236],"R\u00b2":[239],"4.4%":[241],"compared":[242],"conventional":[244],"models.":[246],"These":[247],"findings":[248],"confirm":[249],"harnesses":[255],"information":[258],"significantly":[260],"enhance":[261],"deformation,":[267],"offering":[268],"valuable":[269],"theoretical":[270],"insights":[271],"data":[273],"support":[274],"infrastructure":[280],"projects":[281],"such":[282],"as":[283]},"counts_by_year":[],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-11-04T00:00:00"}
