Search results for "error propagation"
showing 4 items of 4 documents
The effect of automated taxa identification errors on biological indices
2017
In benthic macroinvertebrate biomonitoring systems, the target is to determine the status of ecosystems based on several biological indices. To increase cost-efficiency, computer-based taxa identification for image data has recently been developed. Taxa identification errors can, however, have strong effects on the indices and thus on the determination of the ecological status. In order to shift the biomonitoring process towards automated expert systems, we need a clear understanding on the bias caused by automation. In this paper, we examine eleven classification methods in the case of macroinvertebrate image data and show how their classification errors propagate into different biological…
Uncertainty propagation within the UNEDF models
2016
The parameters of the nuclear energy density have to be adjusted to experimental data. As a result they carry certain uncertainty which then propagates to calculated values of observables. In the present work we quantify the statistical uncertainties of binding energies, proton quadrupole moments, and proton matter radius for three UNEDF Skyrme energy density functionals by taking advantage of the knowledge of the model parameter uncertainties. We find that the uncertainty of UNEDF models increases rapidly when going towards proton or neutron rich nuclei. We also investigate the impact of each model parameter on the total error budget.
Error propagation from line parameters to spectra simulations. Illustration on high temperature methane.
2010
Astrophysical investigations generally need both complete and accurate spectroscopic databases. Despite continuous efforts in experimental and theoretical spectroscopic investigations, the lack of data in some spectral regions of interest is one of the main limitation of the presently available spectroscopic databases. Unfortunately information about missing data relevant to specific experimental conditions is rarely directly accessible from spectroscopic databases (focusing naturally on available data). Such information relies essentially on theoretical investigations which are equally limited to the present state of the art of modelling. The purpose of the talk is to show how multi-resolu…
Improving statistical classification methods and ecological status assessment for river macroinvertebrates
2016
Aquatic ecosystems are facing a growing number of human-induced stressors and the need to implement more biomonitoring to assess the ecological status of water bodies is eminent. This dissertation aims at providing tools to reduce the costs and improve the accuracy of freshwater benthic macroinvertebrate biomonitoring. To improve the cost-e ciency, we consider automated classi cation and develop a novel classi er suitable for complex macroinvertebrate image data. To enhance the accuracy of macroinvertebrate biomonitoring, we study the statistical properties of the Percent Model A nity index crucial to current Finnish biomonitoring and the factors a ecting these statistics. Finally, we perfo…