L. Xingpo, Luca Muzi, Chai Yaozhi, Tan Jue, Gao Jinyan
{"title":"基于SVM代理模型的HSPF水文参数敏感性、优化及不确定性评价综合框架——以青龙河流域为例","authors":"L. Xingpo, Luca Muzi, Chai Yaozhi, Tan Jue, Gao Jinyan","doi":"10.1016/j.envsoft.2021.105126","DOIUrl":null,"url":null,"abstract":"","PeriodicalId":12033,"journal":{"name":"Environ. Model. Softw.","volume":"3 1","pages":"105126"},"PeriodicalIF":0.0000,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":"{\"title\":\"A comprehensive framework for HSPF hydrological parameter sensitivity, optimization and uncertainty evaluation based on SVM surrogate model- A case study in Qinglong River watershed, China\",\"authors\":\"L. Xingpo, Luca Muzi, Chai Yaozhi, Tan Jue, Gao Jinyan\",\"doi\":\"10.1016/j.envsoft.2021.105126\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\",\"PeriodicalId\":12033,\"journal\":{\"name\":\"Environ. Model. Softw.\",\"volume\":\"3 1\",\"pages\":\"105126\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"16\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Environ. Model. Softw.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1016/j.envsoft.2021.105126\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Environ. Model. Softw.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1016/j.envsoft.2021.105126","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A comprehensive framework for HSPF hydrological parameter sensitivity, optimization and uncertainty evaluation based on SVM surrogate model- A case study in Qinglong River watershed, China