Vis enkel innførsel

dc.contributor.authorUssif, Al-Amin M.
dc.contributor.authorSandal, Leif Kristoffer
dc.contributor.authorSteinshamn, Stein Ivar
dc.date.accessioned2006-07-14T07:56:23Z
dc.date.available2006-07-14T07:56:23Z
dc.date.issued2000-05
dc.identifier.issn1500-4066
dc.identifier.urihttp://hdl.handle.net/11250/163743
dc.description.abstractThis paper combines the new and elegant technique of inverse methods and a Monte Carlo procedure to analyze real data for the Norwegian cod fishery (NCF) stock. A simple nonlinear dynamic resource model is calibrated to real time series of observations using the adjoint parameter estimation method of data assimilation and the Monte Carlo technique. By exploring the efficient features of the adjoint technique coupled with the Monte Carlo method, optimal or best parameter estimates together with their error statistics are obtained. Thereafter, the weak constraint formulation resulting in a stochastic ordinary differential equation (SODE) is used to find an improved estimate of the dynamical variable(s). Empirical results show that the average fishing mortality imposed on the NCF stock is 16 % more than the intrinsic growth rate of the biological species.en
dc.format.extent207220 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoengen
dc.publisherNorwegian School of Economics and Business Administration. Department of Finance and Management Scienceen
dc.relation.ispartofseriesDiscussion paperen
dc.relation.ispartofseries2000:6en
dc.titleAssimilation of real time series data into a dynamic bioeconomic fisheries model : an application to the Norwegian cod fishery stocken
dc.typeWorking paperen


Tilhørende fil(er)

Thumbnail

Denne innførselen finnes i følgende samling(er)

Vis enkel innførsel