Abstract：
:A non-traditional approach of fitting dynamic resource biomass models to data is developed in this paper. A variational adjoint technique is used for dynamic parameter estimation. In the variational formulation, a cost function measuring the distance between the model solution and the observations is minimized. The data assimilation method provides a novel and computationally efficient procedure for combining all available information, i.e., the data and the model in the analysis of a resource system. This technique will be used to analyze data for the North-east Arctic cod stock. Two alternative population growth models: the logistic and the Gompertz model are used for estimating parameters of simple bioeconomic models by the method of constrained least squares. Estimates of the parameters of the models dynamics are reasonable and can be accepted. The main inference from the work is that the average fishing mortality is found to be significantly above the maximum sustainable yield value.
journal_name
Math Bioscijournal_title
Mathematical biosciencesauthors
Ussif AA,Sandal LK,Steinshamn SIdoi
10.1016/s0025-5564(02)00178-5subject
Has Abstractpub_date
2003-03-01 00:00:00pages
67-79issue
1eissn
0025-5564issn
1879-3134pii
S0025556402001785journal_volume
182pub_type
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journal_title：Mathematical biosciences
pub_type： 杂志文章
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pub_type： 杂志文章
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更新日期：2010-06-01 00:00:00
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journal_title：Mathematical biosciences
pub_type： 杂志文章
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journal_title：Mathematical biosciences
pub_type： 杂志文章
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更新日期：2008-05-01 00:00:00
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pub_type： 杂志文章,评审
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