Linked Life Data

14768558

Source:http://linkedlifedata.com/resource/pubmed/id/14768558

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
6
pubmed:dateCreated
2004-2-10
pubmed:abstractText
Parameter identification plays a key role in environmental model application. The optimization method is one of the earliest and most widely used methods. However, as the parameters by optimization may not fully fit the observations, there is a risk that the errors may be enhanced in the decision-make stage. With this deficiency in consideration, the RSA and GLUE algorithms search for the feasible parameters not only to the optimum but also around the neighbors. The difference between RSA and GLUE is that the RSA accepts the estimated parameters equally as the candidates for application; while the GLUE keeps the difference among the parameters as measured by likelihood. In addition for parameter identification, both RSA and GLUE are efficient tools for global sensitivity analysis.
pubmed:language
chi
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Nov
pubmed:issn
0250-3301
pubmed:author
pubmed:issnType
Print
pubmed:volume
24
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
9-15
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
2003
pubmed:articleTitle
[Comparison of optimum, RSA and GLUE methods in parameter identification of a nonlinear environmental model].
pubmed:affiliation
Department of Environmental Sciences and Engineering, Tsinghua University, Beijing 100084, China.
pubmed:publicationType
Journal Article, Comparative Study, English Abstract, Research Support, Non-U.S. Gov't