{"id":"https://openalex.org/W3109171118","doi":"https://doi.org/10.3390/rs12233854","title":"Combining Evolutionary Algorithms and Machine Learning Models in Landslide Susceptibility Assessments","display_name":"Combining Evolutionary Algorithms and Machine Learning Models in Landslide Susceptibility Assessments","publication_year":2020,"publication_date":"2020-11-25","ids":{"openalex":"https://openalex.org/W3109171118","doi":"https://doi.org/10.3390/rs12233854","mag":"3109171118"},"language":"en","primary_location":{"id":"doi:10.3390/rs12233854","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs12233854","pdf_url":"https://www.mdpi.com/2072-4292/12/23/3854/pdf?version=1606291526","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"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":"Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/12/23/3854/pdf?version=1606291526","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100719254","display_name":"Wei Chen","orcid":"https://orcid.org/0000-0002-5825-1422"},"institutions":[{"id":"https://openalex.org/I110440473","display_name":"Xi'an University of Science and Technology","ror":"https://ror.org/046fkpt18","country_code":"CN","type":"education","lineage":["https://openalex.org/I110440473"]},{"id":"https://openalex.org/I211433327","display_name":"Ministry of Natural Resources","ror":"https://ror.org/02kxqx159","country_code":"CN","type":"government","lineage":["https://openalex.org/I211433327","https://openalex.org/I4210127390"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Chen","raw_affiliation_strings":["College of Geology and Environment, Xi\u2019an University of Science and Technology, Xi\u2019an 710054, China","Key Laboratory of Coal Resources Exploration and Comprehensive Utilization, Ministry of Natural Resources, Xi\u2019an 710021, China","Key Laboratory of Coal Resources Exploration and Comprehensive Utilization, Ministry of Natural Resources, Xi'an 710021, China","College of Geology and Environment, Xi'an University of Science and Technology, Xi'an 710054, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Geology and Environment, Xi\u2019an University of Science and Technology, Xi\u2019an 710054, China","institution_ids":["https://openalex.org/I110440473"]},{"raw_affiliation_string":"Key Laboratory of Coal Resources Exploration and Comprehensive Utilization, Ministry of Natural Resources, Xi\u2019an 710021, China","institution_ids":["https://openalex.org/I211433327"]},{"raw_affiliation_string":"Key Laboratory of Coal Resources Exploration and Comprehensive Utilization, Ministry of Natural Resources, Xi'an 710021, China","institution_ids":["https://openalex.org/I211433327"]},{"raw_affiliation_string":"College of Geology and Environment, Xi'an University of Science and Technology, Xi'an 710054, China","institution_ids":["https://openalex.org/I110440473"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101592930","display_name":"Yunzhi Chen","orcid":"https://orcid.org/0000-0001-5917-3836"},"institutions":[{"id":"https://openalex.org/I110440473","display_name":"Xi'an University of Science and Technology","ror":"https://ror.org/046fkpt18","country_code":"CN","type":"education","lineage":["https://openalex.org/I110440473"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunzhi Chen","raw_affiliation_strings":["College of Geology and Environment, Xi\u2019an University of Science and Technology, Xi\u2019an 710054, China","College of Geology and Environment, Xi'an University of Science and Technology, Xi'an 710054, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Geology and Environment, Xi\u2019an University of Science and Technology, Xi\u2019an 710054, China","institution_ids":["https://openalex.org/I110440473"]},{"raw_affiliation_string":"College of Geology and Environment, Xi'an University of Science and Technology, Xi'an 710054, China","institution_ids":["https://openalex.org/I110440473"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056283943","display_name":"Paraskevas Tsangaratos","orcid":"https://orcid.org/0000-0002-7396-4754"},"institutions":[{"id":"https://openalex.org/I174458059","display_name":"National Technical University of Athens","ror":"https://ror.org/03cx6bg69","country_code":"GR","type":"education","lineage":["https://openalex.org/I174458059"]}],"countries":["GR"],"is_corresponding":true,"raw_author_name":"Paraskevas Tsangaratos","raw_affiliation_strings":["Laboratory of Engineering Geology and Hydrogeology, Department of Geological Sciences, School of Mining and Metallurgical Engineering, National Technical University of Athens, 15780 Zografou, Greece"],"raw_orcid":"https://orcid.org/0000-0002-7396-4754","affiliations":[{"raw_affiliation_string":"Laboratory of Engineering Geology and Hydrogeology, Department of Geological Sciences, School of Mining and Metallurgical Engineering, National Technical University of Athens, 15780 Zografou, Greece","institution_ids":["https://openalex.org/I174458059"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074740921","display_name":"Ioanna Ilia","orcid":"https://orcid.org/0000-0002-4436-4784"},"institutions":[{"id":"https://openalex.org/I174458059","display_name":"National Technical University of Athens","ror":"https://ror.org/03cx6bg69","country_code":"GR","type":"education","lineage":["https://openalex.org/I174458059"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Ioanna Ilia","raw_affiliation_strings":["Laboratory of Engineering Geology and Hydrogeology, Department of Geological Sciences, School of Mining and Metallurgical Engineering, National Technical University of Athens, 15780 Zografou, Greece"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Laboratory of Engineering Geology and Hydrogeology, Department of Geological Sciences, School of Mining and Metallurgical Engineering, National Technical University of Athens, 15780 Zografou, Greece","institution_ids":["https://openalex.org/I174458059"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100411598","display_name":"Xiaojing Wang","orcid":"https://orcid.org/0000-0002-5596-1488"},"institutions":[{"id":"https://openalex.org/I110440473","display_name":"Xi'an University of Science and Technology","ror":"https://ror.org/046fkpt18","country_code":"CN","type":"education","lineage":["https://openalex.org/I110440473"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaojing Wang","raw_affiliation_strings":["College of Geology and Environment, Xi\u2019an University of Science and Technology, Xi\u2019an 710054, China","College of Geology and Environment, Xi'an University of Science and Technology, Xi'an 710054, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Geology and Environment, Xi\u2019an University of Science and Technology, Xi\u2019an 710054, China","institution_ids":["https://openalex.org/I110440473"]},{"raw_affiliation_string":"College of Geology and Environment, Xi'an University of Science and Technology, Xi'an 710054, China","institution_ids":["https://openalex.org/I110440473"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5056283943"],"corresponding_institution_ids":["https://openalex.org/I174458059"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":23.6545,"has_fulltext":true,"cited_by_count":106,"citation_normalized_percentile":{"value":0.99447386,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"12","issue":"23","first_page":"3854","last_page":"3854"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10535","display_name":"Landslides and related hazards","score":1.0,"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":1.0,"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/T12729","display_name":"Tree Root and Stability Studies","score":0.9800000190734863,"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/T10889","display_name":"Soil erosion and sediment transport","score":0.9679999947547913,"subfield":{"id":"https://openalex.org/subfields/1111","display_name":"Soil Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/particle-swarm-optimization","display_name":"Particle swarm optimization","score":0.6974278092384338},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.669464647769928},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.583267331123352},{"id":"https://openalex.org/keywords/elevation","display_name":"Elevation (ballistics)","score":0.5757219791412354},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5584701895713806},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5427641272544861},{"id":"https://openalex.org/keywords/genetic-algorithm","display_name":"Genetic algorithm","score":0.5305858850479126},{"id":"https://openalex.org/keywords/curvature","display_name":"Curvature","score":0.5230758786201477},{"id":"https://openalex.org/keywords/evolutionary-algorithm","display_name":"Evolutionary algorithm","score":0.5221384167671204},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5128607749938965},{"id":"https://openalex.org/keywords/topographic-wetness-index","display_name":"Topographic Wetness Index","score":0.5026535987854004},{"id":"https://openalex.org/keywords/landslide","display_name":"Landslide","score":0.49274709820747375},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4820183515548706},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4807322025299072},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.4700298011302948},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.23474982380867004},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19359245896339417},{"id":"https://openalex.org/keywords/geomorphology","display_name":"Geomorphology","score":0.13401490449905396}],"concepts":[{"id":"https://openalex.org/C85617194","wikidata":"https://www.wikidata.org/wiki/Q2072794","display_name":"Particle swarm optimization","level":2,"score":0.6974278092384338},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.669464647769928},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.583267331123352},{"id":"https://openalex.org/C37054046","wikidata":"https://www.wikidata.org/wiki/Q641888","display_name":"Elevation (ballistics)","level":2,"score":0.5757219791412354},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5584701895713806},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5427641272544861},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.5305858850479126},{"id":"https://openalex.org/C195065555","wikidata":"https://www.wikidata.org/wiki/Q214881","display_name":"Curvature","level":2,"score":0.5230758786201477},{"id":"https://openalex.org/C159149176","wikidata":"https://www.wikidata.org/wiki/Q14489129","display_name":"Evolutionary algorithm","level":2,"score":0.5221384167671204},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5128607749938965},{"id":"https://openalex.org/C2776898743","wikidata":"https://www.wikidata.org/wiki/Q18353408","display_name":"Topographic Wetness Index","level":3,"score":0.5026535987854004},{"id":"https://openalex.org/C186295008","wikidata":"https://www.wikidata.org/wiki/Q167903","display_name":"Landslide","level":2,"score":0.49274709820747375},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4820183515548706},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4807322025299072},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.4700298011302948},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.23474982380867004},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19359245896339417},{"id":"https://openalex.org/C114793014","wikidata":"https://www.wikidata.org/wiki/Q52109","display_name":"Geomorphology","level":1,"score":0.13401490449905396},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs12233854","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs12233854","pdf_url":"https://www.mdpi.com/2072-4292/12/23/3854/pdf?version=1606291526","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"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":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:bf12cf2ac45e4268bf41b0890f3ea4d5","is_oa":true,"landing_page_url":"https://doaj.org/article/bf12cf2ac45e4268bf41b0890f3ea4d5","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":"Remote Sensing, Vol 12, Iss 23, p 3854 (2020)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/12/23/3854/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs12233854","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"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":"Remote Sensing; Volume 12; Issue 23; Pages: 3854","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs12233854","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs12233854","pdf_url":"https://www.mdpi.com/2072-4292/12/23/3854/pdf?version=1606291526","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"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":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3109171118.pdf","grobid_xml":"https://content.openalex.org/works/W3109171118.grobid-xml"},"referenced_works_count":100,"referenced_works":["https://openalex.org/W49513413","https://openalex.org/W116615339","https://openalex.org/W174072732","https://openalex.org/W255189610","https://openalex.org/W1057892209","https://openalex.org/W1513618424","https://openalex.org/W1973106681","https://openalex.org/W1978784463","https://openalex.org/W1979486410","https://openalex.org/W1984065426","https://openalex.org/W1996933066","https://openalex.org/W2002620848","https://openalex.org/W2006968845","https://openalex.org/W2012118327","https://openalex.org/W2013713766","https://openalex.org/W2017145427","https://openalex.org/W2019957091","https://openalex.org/W2026492654","https://openalex.org/W2028124403","https://openalex.org/W2035161020","https://openalex.org/W2037768558","https://openalex.org/W2039985772","https://openalex.org/W2053927411","https://openalex.org/W2056214587","https://openalex.org/W2058294106","https://openalex.org/W2061940746","https://openalex.org/W2063987149","https://openalex.org/W2066924236","https://openalex.org/W2075513266","https://openalex.org/W2080979633","https://openalex.org/W2091787388","https://openalex.org/W2097698267","https://openalex.org/W2105714409","https://openalex.org/W2107822587","https://openalex.org/W2119843603","https://openalex.org/W2125472389","https://openalex.org/W2134955829","https://openalex.org/W2143192068","https://openalex.org/W2143296882","https://openalex.org/W2169439425","https://openalex.org/W2221487567","https://openalex.org/W2236234032","https://openalex.org/W2336394836","https://openalex.org/W2350578059","https://openalex.org/W2423094380","https://openalex.org/W2489814317","https://openalex.org/W2524483710","https://openalex.org/W2541541850","https://openalex.org/W2543580944","https://openalex.org/W2567854072","https://openalex.org/W2592104387","https://openalex.org/W2606572359","https://openalex.org/W2611950291","https://openalex.org/W2621028994","https://openalex.org/W2738420143","https://openalex.org/W2770617885","https://openalex.org/W2775745878","https://openalex.org/W2789099021","https://openalex.org/W2793831793","https://openalex.org/W2798214660","https://openalex.org/W2802780461","https://openalex.org/W2804841721","https://openalex.org/W2888231268","https://openalex.org/W2905155550","https://openalex.org/W2909103422","https://openalex.org/W2909188960","https://openalex.org/W2912361013","https://openalex.org/W2913214568","https://openalex.org/W2938012181","https://openalex.org/W2955022329","https://openalex.org/W2971304035","https://openalex.org/W2981581709","https://openalex.org/W2987883775","https://openalex.org/W2995502771","https://openalex.org/W2996342798","https://openalex.org/W2998709485","https://openalex.org/W2999310044","https://openalex.org/W3001758897","https://openalex.org/W3007086118","https://openalex.org/W3009221451","https://openalex.org/W3009350425","https://openalex.org/W3010735201","https://openalex.org/W3015539238","https://openalex.org/W3027160207","https://openalex.org/W3032560352","https://openalex.org/W3032913569","https://openalex.org/W3035238198","https://openalex.org/W3038871125","https://openalex.org/W3040332201","https://openalex.org/W3041064370","https://openalex.org/W3042732618","https://openalex.org/W3047180133","https://openalex.org/W3049181801","https://openalex.org/W3049651666","https://openalex.org/W4210949798","https://openalex.org/W4233518571","https://openalex.org/W4252684946","https://openalex.org/W6607128524","https://openalex.org/W6676247742","https://openalex.org/W6682642761"],"related_works":["https://openalex.org/W2389676928","https://openalex.org/W3169474304","https://openalex.org/W2369104181","https://openalex.org/W3201652628","https://openalex.org/W4212972401","https://openalex.org/W2389287188","https://openalex.org/W3081499580","https://openalex.org/W2615020820","https://openalex.org/W3106883776","https://openalex.org/W2950100253"],"abstract_inverted_index":{"The":[0,121],"main":[1],"objective":[2],"of":[3,55,123,186],"the":[4,42,52,109,112,124,136,140,147,156,161,165,173,179,184],"present":[5],"study":[6,125],"is":[7,48],"to":[8,25,50,97,100],"introduce":[9],"a":[10,27,37],"novel":[11],"predictive":[12],"model":[13,138,158,163],"that":[14,127,197],"combines":[15],"evolutionary":[16,193],"algorithms":[17,32,195],"and":[18,63,76,103,189,196],"machine":[19],"learning":[20,142],"(ML)":[21],"models,":[22,58],"so":[23],"as":[24,36,208],"construct":[26],"landslide":[28,205],"susceptibility":[29,206],"map.":[30],"Genetic":[31],"(GA)":[33],"are":[34,106],"used":[35,49,203],"feature":[38,187],"selection":[39,188],"method,":[40],"whereas":[41],"particle":[43],"swarm":[44],"optimization":[45,194],"(PSO)":[46],"method":[47],"optimize":[51],"structural":[53],"parameters":[54],"two":[56],"ML":[57,129,181],"support":[59],"vector":[60],"machines":[61],"(SVM)":[62],"artificial":[64],"neural":[65],"network":[66],"(ANN).":[67],"A":[68],"well-defined":[69],"spatial":[70],"database,":[71],"which":[72],"included":[73],"335":[74],"landslides":[75],"twelve":[77],"landslide-related":[78],"variables":[79],"(elevation,":[80],"slope":[81,83],"angle,":[82],"aspect,":[84],"curvature,":[85,87,89],"plan":[86],"profile":[88],"topographic":[90],"wetness":[91],"index,":[92,95],"stream":[93],"power":[94],"distance":[96,99],"faults,":[98],"river,":[101],"lithology,":[102],"hydrological":[104],"cover)":[105],"considered":[107],"for":[108,204],"analysis,":[110],"in":[111,117],"Achaia":[113],"Regional":[114],"Unit":[115],"located":[116],"Northern":[118],"Peloponnese,":[119],"Greece.":[120],"outcome":[122],"illustrates":[126],"both":[128],"models":[130,182],"have":[131],"an":[132,209],"excellent":[133],"performance,":[134],"with":[135],"SVM":[137,174],"achieving":[139],"highest":[141,166],"accuracy":[143,168],"(0.977":[144],"area":[145],"under":[146],"receiver":[148],"operating":[149],"characteristic":[150],"curve":[151],"value":[152],"(AUC)),":[153],"followed":[154,171],"by":[155,172],"ANN":[157,162],"(0.969).":[159],"However,":[160],"shows":[164],"prediction":[167],"(0.800":[169],"AUC),":[170],"(0.750":[175],"AUC)":[176],"model.":[177],"Overall,":[178],"proposed":[180],"highlights":[183],"necessity":[185],"tuning":[190],"procedures":[191],"via":[192],"such":[198],"approaches":[199],"could":[200],"be":[201],"successfully":[202],"mapping":[207],"alternative":[210],"investigation":[211],"tool.":[212]},"counts_by_year":[{"year":2026,"cited_by_count":9},{"year":2025,"cited_by_count":18},{"year":2024,"cited_by_count":20},{"year":2023,"cited_by_count":18},{"year":2022,"cited_by_count":21},{"year":2021,"cited_by_count":19},{"year":2020,"cited_by_count":1}],"updated_date":"2026-06-17T08:01:34.144755","created_date":"2020-12-07T00:00:00"}
