{"id":"https://openalex.org/W4387803049","doi":"https://doi.org/10.1109/igarss52108.2023.10281586","title":"Recommendation of Landslide Treatment Measures Based on Random Forest","display_name":"Recommendation of Landslide Treatment Measures Based on Random Forest","publication_year":2023,"publication_date":"2023-07-16","ids":{"openalex":"https://openalex.org/W4387803049","doi":"https://doi.org/10.1109/igarss52108.2023.10281586"},"language":"en","primary_location":{"id":"doi:10.1109/igarss52108.2023.10281586","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/igarss52108.2023.10281586","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},"type":"conference-paper","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/A5111060304","display_name":"Maosheng Lina","orcid":null},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Maosheng Lina","raw_affiliation_strings":["University of Electronic Science and Technology of China,School of Resources and Environment,Chengdu,PRC,611731"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China,School of Resources and Environment,Chengdu,PRC,611731","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093097168","display_name":"Xinglong Liua","orcid":null},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinglong Liua","raw_affiliation_strings":["University of Electronic Science and Technology of China,School of Resources and Environment,Chengdu,PRC,611731"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China,School of Resources and Environment,Chengdu,PRC,611731","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093097169","display_name":"Mingcang Zhub","orcid":null},"institutions":[{"id":"https://openalex.org/I4210135981","display_name":"Louisiana Department of Natural Resources","ror":"https://ror.org/03n7hja66","country_code":"US","type":"government","lineage":["https://openalex.org/I4210135981"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mingcang Zhub","raw_affiliation_strings":["Department of Natural Resources of Sichuan Province,Chengdu,PRC,610072"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Natural Resources of Sichuan Province,Chengdu,PRC,610072","institution_ids":["https://openalex.org/I4210135981"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093097170","display_name":"Guoqing Zhouc","orcid":null},"institutions":[{"id":"https://openalex.org/I38706770","display_name":"Guilin University of Technology","ror":"https://ror.org/03z391397","country_code":"CN","type":"education","lineage":["https://openalex.org/I38706770"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guoqing Zhouc","raw_affiliation_strings":["Guilin University of Technology,Guangxi Key Laboratory for Spatial Information and Geomatics,Guilin,PRC,541004"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guilin University of Technology,Guangxi Key Laboratory for Spatial Information and Geomatics,Guilin,PRC,541004","institution_ids":["https://openalex.org/I38706770"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083627327","display_name":"Zezhong Zheng","orcid":"https://orcid.org/0000-0002-5615-5015"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zezhong Zheng","raw_affiliation_strings":["University of Electronic Science and Technology of China,School of Resources and Environment,Chengdu,PRC,611731"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China,School of Resources and Environment,Chengdu,PRC,611731","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093097171","display_name":"Zhanyong Hed","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhanyong Hed","raw_affiliation_strings":["Sichuan Research Institute for Eco-System Restoration &amp; Geo-Hazard Prevention,Chengdu,PRC,610081"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sichuan Research Institute for Eco-System Restoration &amp; Geo-Hazard Prevention,Chengdu,PRC,610081","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093097172","display_name":"Shuang Yua","orcid":null},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuang Yua","raw_affiliation_strings":["University of Electronic Science and Technology of China,School of Resources and Environment,Chengdu,PRC,611731"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China,School of Resources and Environment,Chengdu,PRC,611731","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5093097173","display_name":"Xuefeng Yange","orcid":null},"institutions":[{"id":"https://openalex.org/I4210135994","display_name":"China Railway Group (China)","ror":"https://ror.org/03za3eq42","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210135994"]},{"id":"https://openalex.org/I4387154168","display_name":"China Railway Eryuan Engineering Group Co.","ror":"https://ror.org/003hg6k65","country_code":null,"type":"company","lineage":["https://openalex.org/I4210135994","https://openalex.org/I4387154168"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuefeng Yange","raw_affiliation_strings":["China Railway Eryuan Engineering Group Co., LTD,Chengdu,610031"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Railway Eryuan Engineering Group Co., LTD,Chengdu,610031","institution_ids":["https://openalex.org/I4210135994","https://openalex.org/I4387154168"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"26","issue":null,"first_page":"6053","last_page":"6056"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10535","display_name":"Landslides and related hazards","score":0.9998999834060669,"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":0.9998999834060669,"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/T10930","display_name":"Flood Risk Assessment and Management","score":0.9136000275611877,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"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/T10644","display_name":"Cryospheric studies and observations","score":0.90829998254776,"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/landslide","display_name":"Landslide","score":0.915402352809906},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.8687266111373901},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5853171348571777},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5185947418212891},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5016772747039795},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.49741819500923157},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.4882924556732178},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.43712788820266724},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.40651291608810425},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40457385778427124},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3953872323036194},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.38095617294311523},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3674476146697998},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2300701141357422},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.18513885140419006},{"id":"https://openalex.org/keywords/geotechnical-engineering","display_name":"Geotechnical engineering","score":0.13807952404022217}],"concepts":[{"id":"https://openalex.org/C186295008","wikidata":"https://www.wikidata.org/wiki/Q167903","display_name":"Landslide","level":2,"score":0.915402352809906},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.8687266111373901},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5853171348571777},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5185947418212891},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5016772747039795},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.49741819500923157},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.4882924556732178},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.43712788820266724},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.40651291608810425},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40457385778427124},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3953872323036194},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.38095617294311523},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3674476146697998},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2300701141357422},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.18513885140419006},{"id":"https://openalex.org/C187320778","wikidata":"https://www.wikidata.org/wiki/Q1349130","display_name":"Geotechnical engineering","level":1,"score":0.13807952404022217},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss52108.2023.10281586","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/igarss52108.2023.10281586","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320337504","display_name":"Research and Development","ror":"https://ror.org/027s68j25"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":3,"referenced_works":["https://openalex.org/W2165484089","https://openalex.org/W3205495962","https://openalex.org/W4226449712"],"related_works":["https://openalex.org/W2048488252","https://openalex.org/W4289884158","https://openalex.org/W2940614149","https://openalex.org/W4288365262","https://openalex.org/W2787485953","https://openalex.org/W3217432596","https://openalex.org/W31220157","https://openalex.org/W2312753042","https://openalex.org/W4289356671","https://openalex.org/W2389155397"],"abstract_inverted_index":{"Landslide":[0],"is":[1,32,88],"one":[2],"of":[3,24,29,43,80,95,123,136,177],"the":[4,22,27,38,41,77,92,115,120,124,132,156,178,198],"major":[5],"geological":[6],"disasters":[7],"in":[8,21,40,68,141],"China,":[9],"which":[10],"brings":[11],"huge":[12],"economic":[13],"losses":[14],"to":[15,36,60,75,90,130,185],"our":[16,193],"people":[17],"every":[18],"year.":[19],"However,":[20],"field":[23,42],"landslide":[25,44,65,138,167],"treatment,":[26],"application":[28],"machine":[30,49],"learning":[31],"scarce.":[33],"In":[34],"order":[35],"fill":[37],"gap":[39],"treatment":[45,66,117,139,168],"measures":[46,169],"based":[47],"on":[48,145],"learning.":[50],"Firstly,":[51],"random":[52,108,125,149,158],"forest":[53,99,109,126,150,159],"classification":[54,81,100,162],"or":[55],"regression":[56,96,110,160],"algorithm":[57,101,111,163],"was":[58,73,102,112,128,152,171],"used":[59,74,89],"train":[61],"and":[62,83,154,161],"forecast":[63],"each":[64,137],"measure":[67,140],"this":[69,142],"paper.":[70,143],"Accuracy":[71],"(ACC)":[72],"test":[76,91],"model":[78,93,127,151,164,179,194],"accuracy":[79,94],"algorithm,":[82],"Mean":[84],"Absolute":[85],"Error":[86],"(MAE)":[87],"algorithm.":[97],"Random":[98],"adopted":[103,113],"for":[104,114,166],"non-numerical":[105],"measures.":[106,118],"And":[107],"numerical":[116],"Secondly,":[119],"feature":[121],"importance":[122],"calculated":[129],"obtain":[131],"more":[133],"important":[134],"features":[135],"Based":[144],"this,":[146],"an":[147],"optimized":[148],"constructed,":[153],"finally":[155],"optimal":[157],"suitable":[165],"recommendation":[170],"obtained.":[172],"The":[173,188],"training":[174],"data":[175],"dimensions":[176,184],"were":[180],"reduced":[181],"from":[182],"58":[183],"4-10":[186],"dimensions.":[187],"experimental":[189],"results":[190],"showed":[191],"that":[192],"could":[195],"greatly":[196],"improve":[197],"accuracy.":[199]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
