{"id":"https://openalex.org/W4415722339","doi":"https://doi.org/10.21203/rs.3.rs-7708084/v1","title":"Integrating Signal Decomposition and Intelligent Algorithms for Landslide Displacement Prediction through Multiple Decomposition modal and Clustering","display_name":"Integrating Signal Decomposition and Intelligent Algorithms for Landslide Displacement Prediction through Multiple Decomposition modal and Clustering","publication_year":2025,"publication_date":"2025-10-31","ids":{"openalex":"https://openalex.org/W4415722339","doi":"https://doi.org/10.21203/rs.3.rs-7708084/v1"},"language":"en","primary_location":{"id":"doi:10.21203/rs.3.rs-7708084/v1","doi":"https://doi.org/10.21203/rs.3.rs-7708084/v1","is_oa":true,"landing_page_url":"https://doi.org/10.21203/rs.3.rs-7708084/v1","pdf_url":"https://www.researchsquare.com/article/rs-7708084/latest.pdf","source":{"id":"https://openalex.org/S4306525896","display_name":"Research Square","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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":"Research Square","raw_type":"posted-content"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://www.researchsquare.com/article/rs-7708084/latest.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100388548","display_name":"Limin Li","orcid":"https://orcid.org/0000-0003-4630-431X","observed_orcids":["https://orcid.org/0000-0003-4630-431X"]},"institutions":[{"id":"https://openalex.org/I27599042","display_name":"Xi'an Polytechnic University","ror":"https://ror.org/03442p831","country_code":"CN","type":"education","lineage":["https://openalex.org/I27599042"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Limin Li","raw_affiliation_strings":["Xi\u2019an Polytechnic University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi\u2019an Polytechnic University","institution_ids":["https://openalex.org/I27599042"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103022313","display_name":"Feiyang Chen","orcid":"https://orcid.org/0000-0002-5834-5656","observed_orcids":["https://orcid.org/0000-0002-5834-5656"]},"institutions":[{"id":"https://openalex.org/I27599042","display_name":"Xi'an Polytechnic University","ror":"https://ror.org/03442p831","country_code":"CN","type":"education","lineage":["https://openalex.org/I27599042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feiyang Chen","raw_affiliation_strings":["Xi\u2019an Polytechnic University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi\u2019an Polytechnic University","institution_ids":["https://openalex.org/I27599042"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012712027","display_name":"Chen Gao","orcid":"https://orcid.org/0000-0003-3595-9839","observed_orcids":["https://orcid.org/0000-0003-3595-9839","https://orcid.org/0009-0004-7180-4564"]},"institutions":[{"id":"https://openalex.org/I27599042","display_name":"Xi'an Polytechnic University","ror":"https://ror.org/03442p831","country_code":"CN","type":"education","lineage":["https://openalex.org/I27599042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chen Gao","raw_affiliation_strings":["Xi\u2019an Polytechnic University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi\u2019an Polytechnic University","institution_ids":["https://openalex.org/I27599042"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064029141","display_name":"BIhan Zhang","orcid":"https://orcid.org/0009-0002-4004-6524","observed_orcids":["https://orcid.org/0009-0002-4004-6524"]},"institutions":[{"id":"https://openalex.org/I27599042","display_name":"Xi'an Polytechnic University","ror":"https://ror.org/03442p831","country_code":"CN","type":"education","lineage":["https://openalex.org/I27599042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"BIhan Zhang","raw_affiliation_strings":["Xi\u2019an Polytechnic University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi\u2019an Polytechnic University","institution_ids":["https://openalex.org/I27599042"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109790389","display_name":"B. X. Yu","orcid":"https://orcid.org/0009-0004-6964-9083","observed_orcids":["https://orcid.org/0009-0004-6964-9083"]},"institutions":[{"id":"https://openalex.org/I27599042","display_name":"Xi'an Polytechnic University","ror":"https://ror.org/03442p831","country_code":"CN","type":"education","lineage":["https://openalex.org/I27599042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"BIng Yu","raw_affiliation_strings":["Xi\u2019an Polytechnic University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi\u2019an Polytechnic University","institution_ids":["https://openalex.org/I27599042"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5100388548"],"corresponding_institution_ids":["https://openalex.org/I27599042"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10535","display_name":"Landslides and related hazards","score":0.9932000041007996,"subfield":{"id":"https://openalex.org/subfields/2308","display_name":"Management, Monitoring, Policy and Law"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10535","display_name":"Landslides and related hazards","score":0.9932000041007996,"subfield":{"id":"https://openalex.org/subfields/2308","display_name":"Management, Monitoring, Policy and Law"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13941","display_name":"Geotechnical and Mining Engineering","score":0.0019000000320374966,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/T11490","display_name":"Hydrological Forecasting Using AI","score":0.0005000000237487257,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/landslide-displacement-prediction","display_name":"landslide displacement prediction","score":0.9990000128746033},{"id":"https://openalex.org/keywords/signal-decomposition","display_name":"signal decomposition","score":0.7900000214576721},{"id":"https://openalex.org/keywords/ceemdan","display_name":"CEEMDAN","score":0.9919999837875366},{"id":"https://openalex.org/keywords/vmd","display_name":"VMD","score":0.8149999976158142},{"id":"https://openalex.org/keywords/sample-entropy","display_name":"sample entropy","score":0.7950000166893005},{"id":"https://openalex.org/keywords/k-means-clustering","display_name":"K-means clustering","score":0.9679999947547913},{"id":"https://openalex.org/keywords/cnn-bilstm","display_name":"CNN-BiLSTM","score":0.890999972820282},{"id":"https://openalex.org/keywords/improved-sparrow-search-algorithm","display_name":"improved sparrow search algorithm","score":0.7039999961853027},{"id":"https://openalex.org/keywords/hyperparameter-optimization","display_name":"hyperparameter optimization","score":0.9570000171661377}],"concepts":[{"id":"https://openalex.org/C2776537626","wikidata":"https://www.wikidata.org/wiki/Q4047883","display_name":"Long-term prediction","level":2,"score":0.6514999866485596},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5734000205993652},{"id":"https://openalex.org/C107551265","wikidata":"https://www.wikidata.org/wiki/Q1458245","display_name":"Displacement (psychology)","level":2,"score":0.5467000007629395},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.48570001125335693},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.46880000829696655},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.4593999981880188},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.44929999113082886},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.40619999170303345},{"id":"https://openalex.org/C203595873","wikidata":"https://www.wikidata.org/wiki/Q25389927","display_name":"Change detection","level":2,"score":0.40619999170303345},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.3361999988555908},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.3361000120639801},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.3319000005722046},{"id":"https://openalex.org/C186295008","wikidata":"https://www.wikidata.org/wiki/Q167903","display_name":"Landslide","level":2,"score":0.32170000672340393},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3172999918460846},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.3057999908924103},{"id":"https://openalex.org/C2780799671","wikidata":"https://www.wikidata.org/wiki/Q17087362","display_name":"Transient (computer programming)","level":2,"score":0.3003999888896942},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.29350000619888306},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.28540000319480896},{"id":"https://openalex.org/C124681953","wikidata":"https://www.wikidata.org/wiki/Q339062","display_name":"Decomposition","level":2,"score":0.2680000066757202},{"id":"https://openalex.org/C14279187","wikidata":"https://www.wikidata.org/wiki/Q5514012","display_name":"GNSS applications","level":3,"score":0.2678000032901764},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2635999917984009},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.260699987411499}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.21203/rs.3.rs-7708084/v1","doi":"https://doi.org/10.21203/rs.3.rs-7708084/v1","is_oa":true,"landing_page_url":"https://doi.org/10.21203/rs.3.rs-7708084/v1","pdf_url":"https://www.researchsquare.com/article/rs-7708084/latest.pdf","source":{"id":"https://openalex.org/S4306525896","display_name":"Research Square","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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":"Research Square","raw_type":"posted-content"}],"best_oa_location":{"id":"doi:10.21203/rs.3.rs-7708084/v1","doi":"https://doi.org/10.21203/rs.3.rs-7708084/v1","is_oa":true,"landing_page_url":"https://doi.org/10.21203/rs.3.rs-7708084/v1","pdf_url":"https://www.researchsquare.com/article/rs-7708084/latest.pdf","source":{"id":"https://openalex.org/S4306525896","display_name":"Research Square","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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":"Research Square","raw_type":"posted-content"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4415722339.pdf","grobid_xml":"https://content.openalex.org/works/W4415722339.grobid-xml"},"referenced_works_count":14,"referenced_works":["https://openalex.org/W3035386920","https://openalex.org/W3097346376","https://openalex.org/W4285596664","https://openalex.org/W4295845661","https://openalex.org/W4360986054","https://openalex.org/W4377096625","https://openalex.org/W4382138092","https://openalex.org/W4389080370","https://openalex.org/W4391612669","https://openalex.org/W4395010415","https://openalex.org/W4403415962","https://openalex.org/W4403459255","https://openalex.org/W4404045367","https://openalex.org/W4404922606"],"related_works":["https://openalex.org/W4288732391","https://openalex.org/W4313427757","https://openalex.org/W7167056358","https://openalex.org/W4285147137","https://openalex.org/W4281692595","https://openalex.org/W4412731349","https://openalex.org/W3193658206","https://openalex.org/W4399580429","https://openalex.org/W7162806018","https://openalex.org/W4393235311"],"abstract_inverted_index":{"Abstract":[0],"Landslide":[1,14],"displacement":[2,15,48,74],"prediction":[3,69,117,224,293],"is":[4,21,75,84,98,122,187,211,226],"an":[5],"important":[6],"part":[7],"of":[8,45,55,164,207,236,248,270,294,300],"geologic":[9],"disaster":[10],"prevention":[11],"and":[12,29,59,80,91,129,142,174,200,222,255,284],"control.":[13],"in":[16,105,198,297],"the":[17,39,42,53,56,65,72,81,96,102,112,116,119,127,135,145,155,162,168,181,190,194,201,205,208,223,233,237,239,246,256,268,271,279,292,298,301],"Three":[18],"Gorges":[19],"area":[20],"affected":[22],"by":[23,78,124,139,149],"short-term":[24],"factors":[25,137],"such":[26],"as":[27],"rainfall":[28],"reservoir":[30],"level":[31],"fluctuation,":[32],"showing":[33],"obvious":[34],"step-abrupt":[35],"characteristics.":[36],"Aiming":[37],"at":[38],"problem":[40],"that":[41,204,278],"single":[43],"decomposition":[44],"GNSS":[46],"high-frequency":[47],"signal":[49],"easily":[50],"leads":[51],"to":[52,100,179,216,231,245],"mixing":[54],"periodic":[57,82,103,128,209],"term":[58,121,173,176,210],"noise,":[60],"this":[61],"paper":[62],"innovatively":[63],"proposes":[64],"CVSCB":[66],"(CEEMDAN-VMD-SCSSA-CNN-BILSTM)":[67],"hybrid":[68],"model.":[70,273],"Firstly,":[71],"cumulative":[73,182],"adaptively":[76],"decomposed":[77],"CEEMDAN,":[79],"component":[83,104],"recognized":[85],"based":[86,188],"on":[87,189],"Sample":[88],"Entropy":[89],"(SampEn)":[90],"K-means":[92],"clustering;":[93],"following":[94],"that,":[95],"VMD":[97],"used":[99],"decompose":[101],"a":[106,288],"secondary":[107],"way,":[108],"which":[109],"effectively":[110],"separates":[111],"noise":[113],"interference.":[114],"In":[115,229],"stage,":[118],"trend":[120,172,299],"modeled":[123],"ARIMA,":[125],"while":[126],"stochastic":[130],"terms":[131],"are":[132,177],"combined":[133],"with":[134],"influence":[136],"screened":[138],"Spearman's":[140],"correlation,":[141],"input":[143],"into":[144],"CNN-BILSTM":[146],"network":[147],"optimized":[148],"SCSSA":[150],"for":[151,253,267,291],"prediction.":[152],"Among":[153],"them,":[154],"improved":[156],"sparrow":[157],"algorithm":[158],"(SCSSA)":[159],"significantly":[160,227],"improves":[161],"efficiency":[163],"hyperparameter":[165],"optimization.":[166],"Finally,":[167],"predicted":[169,183],"period":[170],"term,":[171],"random":[175],"superimposed":[178],"obtain":[180],"displacement.":[184],"The":[185,274],"validation":[186,269],"daily":[191,240],"data":[192,242,247,259],"from":[193,213,262],"monitoring":[195,241,251,258,265],"point":[196,252,266],"ZD3":[197],"Baijiabao,":[199],"results":[202,276],"show":[203,277],"RMSE":[206],"reduced":[212],"2.5401":[214],"mm":[215,218],"0.3899":[217],"after":[219],"multiple":[220],"decomposition,":[221],"effect":[225],"improved.":[228],"order":[230],"verify":[232],"generalization":[234],"ability":[235],"model,":[238],"were":[243,260],"extended":[244],"Baijiabao":[249],"ZD2":[250],"validation,":[254],"monthly":[257],"adopted":[261],"Xintan":[263],"DTX1":[264],"same":[272],"experimental":[275],"method":[280],"has":[281],"good":[282],"generalization,":[283],"it":[285],"can":[286],"provide":[287],"reliable":[289],"reference":[290],"landslide":[295],"displacements":[296],"step":[302],"change.":[303]},"counts_by_year":[],"updated_date":"2026-11-12T12:28:57.059296","created_date":"2025-10-31T00:00:00"}
