1 resultado para model-based reasoning
em CUNY Academic Works
Filtro por publicador
- ABACUS. Repositorio de Producción Científica - Universidad Europea (1)
- Aberdeen University (2)
- Abertay Research Collections - Abertay University’s repository (1)
- Aberystwyth University Repository - Reino Unido (9)
- Academic Research Repository at Institute of Developing Economies (2)
- AMS Tesi di Dottorato - Alm@DL - Università di Bologna (6)
- AMS Tesi di Laurea - Alm@DL - Università di Bologna (1)
- Aquatic Commons (5)
- Archive of European Integration (1)
- Archivo Digital para la Docencia y la Investigación - Repositorio Institucional de la Universidad del País Vasco (5)
- Aston University Research Archive (21)
- Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (10)
- Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP) (7)
- BORIS: Bern Open Repository and Information System - Berna - Suiça (43)
- Boston University Digital Common (3)
- Brock University, Canada (1)
- Bucknell University Digital Commons - Pensilvania - USA (5)
- Bulgarian Digital Mathematics Library at IMI-BAS (14)
- CaltechTHESIS (2)
- Cambridge University Engineering Department Publications Database (75)
- CentAUR: Central Archive University of Reading - UK (41)
- Chinese Academy of Sciences Institutional Repositories Grid Portal (14)
- CiencIPCA - Instituto Politécnico do Cávado e do Ave, Portugal (1)
- Cochin University of Science & Technology (CUSAT), India (2)
- Collection Of Biostatistics Research Archive (5)
- Comissão Econômica para a América Latina e o Caribe (CEPAL) (1)
- CORA - Cork Open Research Archive - University College Cork - Ireland (2)
- Corvinus Research Archive - The institutional repository for the Corvinus University of Budapest (1)
- CUNY Academic Works (1)
- Dalarna University College Electronic Archive (1)
- Deakin Research Online - Australia (72)
- Department of Computer Science E-Repository - King's College London, Strand, London (5)
- Digital Commons - Michigan Tech (5)
- Digital Commons @ DU | University of Denver Research (1)
- Digital Commons at Florida International University (3)
- Digital Peer Publishing (3)
- DigitalCommons - The University of Maine Research (2)
- DigitalCommons@The Texas Medical Center (4)
- DigitalCommons@University of Nebraska - Lincoln (2)
- Duke University (3)
- eResearch Archive - Queensland Department of Agriculture; Fisheries and Forestry (10)
- FUNDAJ - Fundação Joaquim Nabuco (2)
- Greenwich Academic Literature Archive - UK (17)
- Helda - Digital Repository of University of Helsinki (3)
- Indian Institute of Science - Bangalore - Índia (39)
- Institute of Public Health in Ireland, Ireland (1)
- Institutional Repository of Leibniz University Hannover (1)
- INSTITUTO DE PESQUISAS ENERGÉTICAS E NUCLEARES (IPEN) - Repositório Digital da Produção Técnico Científica - BibliotecaTerezine Arantes Ferra (1)
- Instituto Politécnico de Bragança (1)
- Instituto Politécnico do Porto, Portugal (6)
- Massachusetts Institute of Technology (14)
- National Center for Biotechnology Information - NCBI (7)
- Nottingham eTheses (8)
- Projetos e Dissertações em Sistemas de Informação e Gestão do Conhecimento (1)
- Publishing Network for Geoscientific & Environmental Data (12)
- QSpace: Queen's University - Canada (1)
- QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast (54)
- Queensland University of Technology - ePrints Archive (187)
- RCAAP - Repositório Científico de Acesso Aberto de Portugal (1)
- Repositório Científico da Universidade de Évora - Portugal (13)
- Repositório Científico do Instituto Politécnico de Lisboa - Portugal (3)
- Repositório digital da Fundação Getúlio Vargas - FGV (1)
- Repositório do ISCTE - Instituto Universitário de Lisboa (1)
- Repositório Institucional da Universidade de Aveiro - Portugal (1)
- Repositorio Institucional de la Universidad de Málaga (1)
- Repositorio Institucional de la Universidad Pública de Navarra - Espanha (1)
- Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho" (39)
- RUN (Repositório da Universidade Nova de Lisboa) - FCT (Faculdade de Cienecias e Technologia), Universidade Nova de Lisboa (UNL), Portugal (1)
- SAPIENTIA - Universidade do Algarve - Portugal (1)
- Universidad de Alicante (7)
- Universidad del Rosario, Colombia (5)
- Universidad Politécnica de Madrid (55)
- Universidade Complutense de Madrid (3)
- Universidade de Lisboa - Repositório Aberto (1)
- Universidade do Algarve (1)
- Universidade Estadual Paulista "Júlio de Mesquita Filho" (UNESP) (1)
- Universidade Federal do Rio Grande do Norte (UFRN) (1)
- Universitat de Girona, Spain (12)
- Universitätsbibliothek Kassel, Universität Kassel, Germany (1)
- Université de Lausanne, Switzerland (2)
- Université de Montréal (1)
- Université de Montréal, Canada (6)
- University of Michigan (1)
- University of Queensland eSpace - Australia (21)
- University of Washington (1)
- WestminsterResearch - UK (1)
Resumo:
A procedure for characterizing global uncertainty of a rainfall-runoff simulation model based on using grey numbers is presented. By using the grey numbers technique the uncertainty is characterized by an interval; once the parameters of the rainfall-runoff model have been properly defined as grey numbers, by using the grey mathematics and functions it is possible to obtain simulated discharges in the form of grey numbers whose envelope defines a band which represents the vagueness/uncertainty associated with the simulated variable. The grey numbers representing the model parameters are estimated in such a way that the band obtained from the envelope of simulated grey discharges includes an assigned percentage of observed discharge values and is at the same time as narrow as possible. The approach is applied to a real case study highlighting that a rigorous application of the procedure for direct simulation through the rainfall-runoff model with grey parameters involves long computational times. However, these times can be significantly reduced using a simplified computing procedure with minimal approximations in the quantification of the grey numbers representing the simulated discharges. Relying on this simplified procedure, the conceptual rainfall-runoff grey model is thus calibrated and the uncertainty bands obtained both downstream of the calibration process and downstream of the validation process are compared with those obtained by using a well-established approach, like the GLUE approach, for characterizing uncertainty. The results of the comparison show that the proposed approach may represent a valid tool for characterizing the global uncertainty associable with the output of a rainfall-runoff simulation model.