{"title":"Modeling of landslides susceptibility prediction using deep belief networks with optimized learning rate control","authors":"Qiang Liu, Namkha Norbu","doi":"10.1080/10106049.2024.2322060","DOIUrl":null,"url":null,"abstract":"To overcome critical issues in landslide susceptibility modeling, a multifactor landslide susceptibility prediction model based on deep belief networks (DBN) with optimized learning rate control (L...","PeriodicalId":12532,"journal":{"name":"Geocarto International","volume":"46 1","pages":""},"PeriodicalIF":3.3000,"publicationDate":"2024-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Geocarto International","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1080/10106049.2024.2322060","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
To overcome critical issues in landslide susceptibility modeling, a multifactor landslide susceptibility prediction model based on deep belief networks (DBN) with optimized learning rate control (L...
期刊介绍：
Geocarto International is a professional academic journal serving the world-wide scientific and user community in the fields of remote sensing, GIS, geoscience and environmental sciences. The journal is designed: to promote multidisciplinary research in and application of remote sensing and GIS in geosciences and environmental sciences; to enhance international exchange of information on new developments and applications in the field of remote sensing and GIS and related disciplines; to foster interest in and understanding of science and applications on remote sensing and GIS technologies; and to encourage the publication of timely papers and research results on remote sensing and GIS applications in geosciences and environmental sciences from the world-wide science community.
The journal welcomes contributions on the following: precise, illustrated papers on new developments, technologies and applications of remote sensing; research results in remote sensing, GISciences and related disciplines;
Reports on new and innovative applications and projects in these areas; and assessment and evaluation of new remote sensing and GIS equipment, software and hardware.
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