{"title":"频率比、熵指数和人工神经网络方法在滑坡易感性制图中的比较——以Pınarbaşı/Kastamonu(土耳其北部)为例","authors":"Enes Taşoğlu, S. Abujayyab","doi":"10.1016/b978-0-323-89861-4.00042-7","DOIUrl":null,"url":null,"abstract":"","PeriodicalId":410064,"journal":{"name":"Computers in Earth and Environmental Sciences","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Comparison of the frequency ratio, index of entropy, and artificial neural networks methods for landslide susceptibility mapping: A case study in Pınarbaşı/Kastamonu (North of Turkey)\",\"authors\":\"Enes Taşoğlu, S. Abujayyab\",\"doi\":\"10.1016/b978-0-323-89861-4.00042-7\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\",\"PeriodicalId\":410064,\"journal\":{\"name\":\"Computers in Earth and Environmental Sciences\",\"volume\":\"30 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computers in Earth and Environmental Sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1016/b978-0-323-89861-4.00042-7\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers in Earth and Environmental Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1016/b978-0-323-89861-4.00042-7","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Comparison of the frequency ratio, index of entropy, and artificial neural networks methods for landslide susceptibility mapping: A case study in Pınarbaşı/Kastamonu (North of Turkey)