{"id":"https://openalex.org/W3210270100","doi":"https://doi.org/10.3390/geomatics1040023","title":"Entropy-Based Hybrid Integration of Random Forest and Support Vector Machine for Landslide Susceptibility Analysis","display_name":"Entropy-Based Hybrid Integration of Random Forest and Support Vector Machine for Landslide Susceptibility Analysis","publication_year":2021,"publication_date":"2021-10-26","ids":{"openalex":"https://openalex.org/W3210270100","doi":"https://doi.org/10.3390/geomatics1040023","mag":"3210270100"},"language":"en","primary_location":{"id":"doi:10.3390/geomatics1040023","doi":"https://doi.org/10.3390/geomatics1040023","is_oa":true,"landing_page_url":"https://doi.org/10.3390/geomatics1040023","pdf_url":"https://www.mdpi.com/2673-7418/1/4/23/pdf?version=1635247457","source":{"id":"https://openalex.org/S4210221798","display_name":"Geomatics","issn_l":"2673-7418","issn":["2673-7418"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","norway-1"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Geomatics","raw_type":"journal-article"},"volume":null,"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2673-7418/1/4/23/pdf?version=1635247457","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5023774706","display_name":"Amol Sharma","orcid":"https://orcid.org/0000-0003-1013-9949","observed_orcids":["https://orcid.org/0000-0003-1013-9949"]},"institutions":[{"id":"https://openalex.org/I36909309","display_name":"National Institute of Technology Hamirpur","ror":"https://ror.org/01nc8zs04","country_code":"BD","type":"education","lineage":["https://openalex.org/I36909309","https://openalex.org/I4210152752"]}],"countries":["BD"],"is_corresponding":true,"raw_author_name":"Amol Sharma","raw_affiliation_strings":["Department of Civil Engineering, National Institute of Technology, Hamirpur 177005, Himachal Pradesh, India"],"raw_orcid":"https://orcid.org/0000-0003-1013-9949","affiliations":[{"raw_affiliation_string":"Department of Civil Engineering, National Institute of Technology, Hamirpur 177005, Himachal Pradesh, India","institution_ids":["https://openalex.org/I36909309"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084248029","display_name":"Chander Prakash","orcid":"https://orcid.org/0000-0002-6126-6959","observed_orcids":["https://orcid.org/0000-0002-6126-6959"]},"institutions":[{"id":"https://openalex.org/I36909309","display_name":"National Institute of Technology Hamirpur","ror":"https://ror.org/01nc8zs04","country_code":"BD","type":"education","lineage":["https://openalex.org/I36909309","https://openalex.org/I4210152752"]}],"countries":["BD"],"is_corresponding":false,"raw_author_name":"Chander Prakash","raw_affiliation_strings":["Department of Civil Engineering, National Institute of Technology, Hamirpur 177005, Himachal Pradesh, India"],"raw_orcid":"https://orcid.org/0000-0002-6126-6959","affiliations":[{"raw_affiliation_string":"Department of Civil Engineering, National Institute of Technology, Hamirpur 177005, Himachal Pradesh, India","institution_ids":["https://openalex.org/I36909309"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5048495406","display_name":"V. S. Manivasagam","orcid":"https://orcid.org/0000-0002-6186-8941","observed_orcids":["https://orcid.org/0000-0002-6186-8941"]},"institutions":[{"id":"https://openalex.org/I81556334","display_name":"Amrita Vishwa Vidyapeetham","ror":"https://ror.org/03am10p12","country_code":"IN","type":"education","lineage":["https://openalex.org/I81556334"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"V. Manivasagam","raw_affiliation_strings":["Amrita School of Agricultural Sciences, Amrita Vishwa Vidyapeetham, J. P. Nagar, Arasampalayam, Myleripalayam, Coimbatore 642109, Tamil Nadu, India"],"raw_orcid":"https://orcid.org/0000-0002-6186-8941","affiliations":[{"raw_affiliation_string":"Amrita School of Agricultural Sciences, Amrita Vishwa Vidyapeetham, J. P. Nagar, Arasampalayam, Myleripalayam, Coimbatore 642109, Tamil Nadu, India","institution_ids":["https://openalex.org/I81556334"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5023774706"],"corresponding_institution_ids":["https://openalex.org/I36909309"],"apc_list":{"value":1000,"currency":"CHF","value_usd":1080},"apc_paid":{"value":1000,"currency":"CHF","value_usd":1080},"fwci":4.5506,"has_fulltext":true,"cited_by_count":31,"citation_normalized_percentile":{"value":0.93951019,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"1","issue":"4","first_page":"399","last_page":"416"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10535","display_name":"Landslides and related hazards","score":0.9994999766349792,"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":0.9994999766349792,"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/T11046","display_name":"Geotechnical Engineering and Analysis","score":0.00019999999494757503,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/T12729","display_name":"Tree Root and Stability Studies","score":9.999999747378752e-05,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/landslide-susceptibility-mapping","display_name":"landslide susceptibility mapping","score":0.984000027179718},{"id":"https://openalex.org/keywords/shannon-entropy","display_name":"Shannon entropy","score":0.7419999837875366},{"id":"https://openalex.org/keywords/random-forest","display_name":"random forest","score":0.8840000033378601},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"support vector machine","score":1.0},{"id":"https://openalex.org/keywords/hybrid-machine-learning","display_name":"hybrid machine learning","score":0.6549999713897705},{"id":"https://openalex.org/keywords/feature-selection","display_name":"feature selection","score":0.796999990940094},{"id":"https://openalex.org/keywords/rainfall-induced-landslides","display_name":"rainfall-induced landslides","score":0.8519999980926514},{"id":"https://openalex.org/keywords/landslide-influencing-factors","display_name":"landslide causative factors","score":0.9210000038146973},{"id":"https://openalex.org/keywords/mandi-district","display_name":"Mandi district","score":0.8119999766349792},{"id":"https://openalex.org/keywords/himachal-pradesh","display_name":"Himachal Pradesh","score":0.9760000109672546}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7840023636817932},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.7197690606117249},{"id":"https://openalex.org/C186295008","wikidata":"https://www.wikidata.org/wiki/Q167903","display_name":"Landslide","level":2,"score":0.7079699039459229},{"id":"https://openalex.org/C206041023","wikidata":"https://www.wikidata.org/wiki/Q1751970","display_name":"Wilcoxon signed-rank test","level":3,"score":0.6889611482620239},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.5477733016014099},{"id":"https://openalex.org/C189285262","wikidata":"https://www.wikidata.org/wiki/Q1332350","display_name":"Multicollinearity","level":3,"score":0.5198984146118164},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.49879026412963867},{"id":"https://openalex.org/C58471807","wikidata":"https://www.wikidata.org/wiki/Q327120","display_name":"Receiver operating characteristic","level":2,"score":0.45683830976486206},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44982191920280457},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4327377378940582},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.411260724067688},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40434160828590393},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3963805139064789},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33796465396881104},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.19007793068885803},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.18927627801895142},{"id":"https://openalex.org/C12868164","wikidata":"https://www.wikidata.org/wiki/Q1424533","display_name":"Mann\u2013Whitney U test","level":2,"score":0.12071600556373596},{"id":"https://openalex.org/C187320778","wikidata":"https://www.wikidata.org/wiki/Q1349130","display_name":"Geotechnical engineering","level":1,"score":0.08914336562156677}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/geomatics1040023","doi":"https://doi.org/10.3390/geomatics1040023","is_oa":true,"landing_page_url":"https://doi.org/10.3390/geomatics1040023","pdf_url":"https://www.mdpi.com/2673-7418/1/4/23/pdf?version=1635247457","source":{"id":"https://openalex.org/S4210221798","display_name":"Geomatics","issn_l":"2673-7418","issn":["2673-7418"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","norway-1"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Geomatics","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:2e28895a94034614867c4cf8c1027c07","doi":null,"is_oa":true,"landing_page_url":"https://doaj.org/article/2e28895a94034614867c4cf8c1027c07","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,"listed_in":[],"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":"Geomatics, Vol 1, Iss 4, Pp 399-416 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/geomatics1040023","doi":"https://doi.org/10.3390/geomatics1040023","is_oa":true,"landing_page_url":"https://doi.org/10.3390/geomatics1040023","pdf_url":"https://www.mdpi.com/2673-7418/1/4/23/pdf?version=1635247457","source":{"id":"https://openalex.org/S4210221798","display_name":"Geomatics","issn_l":"2673-7418","issn":["2673-7418"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","norway-1"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Geomatics","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Life on land","score":0.4390000104904175,"id":"https://metadata.un.org/sdg/15"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3210270100.pdf","grobid_xml":"https://content.openalex.org/works/W3210270100.grobid-xml"},"referenced_works_count":74,"referenced_works":["https://openalex.org/W310214239","https://openalex.org/W1003766845","https://openalex.org/W1980725494","https://openalex.org/W1983631475","https://openalex.org/W1989156417","https://openalex.org/W1996735577","https://openalex.org/W2003049509","https://openalex.org/W2004200173","https://openalex.org/W2019957091","https://openalex.org/W2021765639","https://openalex.org/W2022839426","https://openalex.org/W2028124403","https://openalex.org/W2035549409","https://openalex.org/W2044256315","https://openalex.org/W2046361090","https://openalex.org/W2069663627","https://openalex.org/W2087560564","https://openalex.org/W2090292633","https://openalex.org/W2095057310","https://openalex.org/W2126668662","https://openalex.org/W2147167032","https://openalex.org/W2161448538","https://openalex.org/W2269516007","https://openalex.org/W2301435151","https://openalex.org/W2304932561","https://openalex.org/W2346405468","https://openalex.org/W2417137833","https://openalex.org/W2485227433","https://openalex.org/W2524483710","https://openalex.org/W2587950680","https://openalex.org/W2754252800","https://openalex.org/W2789555074","https://openalex.org/W2793729791","https://openalex.org/W2793831793","https://openalex.org/W2798214660","https://openalex.org/W2880239935","https://openalex.org/W2889065082","https://openalex.org/W2890791388","https://openalex.org/W2891576621","https://openalex.org/W2894082056","https://openalex.org/W2901271692","https://openalex.org/W2911424673","https://openalex.org/W2911964244","https://openalex.org/W2912160963","https://openalex.org/W2913214568","https://openalex.org/W2922361723","https://openalex.org/W2922551714","https://openalex.org/W2942378806","https://openalex.org/W2957135778","https://openalex.org/W2969261624","https://openalex.org/W2969688345","https://openalex.org/W2970709330","https://openalex.org/W2978525465","https://openalex.org/W2981581709","https://openalex.org/W2994312904","https://openalex.org/W2995023505","https://openalex.org/W2998709485","https://openalex.org/W3005068726","https://openalex.org/W3005376489","https://openalex.org/W3007086118","https://openalex.org/W3027155096","https://openalex.org/W3032913569","https://openalex.org/W3036091573","https://openalex.org/W3040332201","https://openalex.org/W3041064370","https://openalex.org/W3044200916","https://openalex.org/W3049181801","https://openalex.org/W3082878526","https://openalex.org/W3091882851","https://openalex.org/W3109885934","https://openalex.org/W3115061751","https://openalex.org/W3141979009","https://openalex.org/W3153886279","https://openalex.org/W4239510810"],"related_works":["https://openalex.org/W2901271692","https://openalex.org/W4410825735","https://openalex.org/W2793729791","https://openalex.org/W3164813077","https://openalex.org/W2524483710","https://openalex.org/W3092510885","https://openalex.org/W2580219088","https://openalex.org/W2911253733","https://openalex.org/W2475379415","https://openalex.org/W4280534344"],"abstract_inverted_index":{"Landslide":[0],"susceptibility":[1,23,128,198],"mapping":[2],"is":[3,18,190,193],"a":[4],"crucial":[5],"step":[6],"in":[7],"comprehensive":[8],"landslide":[9,22,119,127,197],"risk":[10],"management.":[11],"The":[12,152,181],"purpose":[13],"of":[14,24,38,56,76,117,161,176,200],"the":[15,21,39,168,187,196],"present":[16],"study":[17],"to":[19,109],"analyze":[20],"Mandi":[25],"district,":[26],"Himachal":[27],"Pradesh,":[28],"India,":[29],"based":[30],"on":[31],"optimum":[32,115],"feature":[33,96],"selection":[34],"and":[35,48,62,69,82,94,104,134,141,149,158,163,173,178,192],"hybrid":[36,132],"integration":[37],"Shannon":[40],"entropy":[41],"(SE)":[42],"model":[43,170,189],"with":[44,156,167,171],"random":[45],"forest":[46],"(RF)":[47],"support":[49],"vector":[50],"machine":[51],"(SVM)":[52],"models.":[53,136],"An":[54,114],"inventory":[55],"1723":[57],"rainfall-induced":[58],"landslides":[59],"was":[60,80,122],"generated":[61],"randomly":[63],"selected":[64,81],"for":[65,84,125,195],"training":[66,157,172],"(1199;":[67],"70%)":[68],"validation":[70,159,174],"(524;":[71],"30%)":[72],"purposes.":[73],"A":[74],"set":[75],"14":[77],"relevant":[78],"factors":[79,87,121],"checked":[83],"multicollinearity.":[85],"These":[86,137],"were":[88,107,139],"first":[89],"ranked":[90],"using":[91,131,143],"Information":[92],"Gain":[93],"Chi-square":[95],"ranking":[97],"algorithms.":[98],"Furthermore,":[99],"Wilcoxon":[100],"Signed":[101],"Rank":[102],"Test":[103],"One-Sample":[105],"T-Test":[106],"applied":[108],"check":[110],"their":[111],"statistical":[112],"significance.":[113],"subset":[116],"11":[118],"causative":[120],"then":[123],"used":[124],"generating":[126],"maps":[129],"(LSM)":[130],"SE-RF":[133,153,188],"SE-SVM":[135,169],"LSM\u2019s":[138],"validated":[140],"compared":[142,166],"receiver":[144],"operating":[145],"characteristic":[146],"(ROC)":[147],"curves":[148],"performance":[150],"matrices.":[151],"performed":[154],"better":[155,191],"accuracies":[160,175],"96.93%":[162],"88.94%,":[164],"respectively,":[165],"94.05%":[177],"82.4%,":[179],"respectively.":[180],"prediction":[182],"matrices":[183],"also":[184],"confirmed":[185],"that":[186],"recommended":[194],"analysis":[199],"similar":[201],"mountainous":[202],"regions":[203],"worldwide.":[204]},"counts_by_year":[{"year":2026,"cited_by_count":7},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":4}],"updated_date":"2026-11-03T10:50:19.383937","created_date":"2021-11-08T00:00:00"}