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National Repository of Grey Literature 3 records found  Search took 0.01 seconds. 
Data reconciliation and gross error detection
 Nováček, Adam ; Šomplák, Radovan (referee) ; Touš, Michal (advisor)
Operational data are used for control and optimization of a process in industrial and energy plants are used. Data provided from measurement are affected by errors arising from uncertainty of measurement (imprecision of measuring instruments). Data reconciliation provides us more precise variables which give us the opportunity to better optimize and achieve higher economic gains. The objective of this bachelor's thesis was to study the issue of data reconciliation of measurement and gross error detection in measurement variables. This work is divided into two parts. The first part is theoretical, describing measurement errors, solution methods for data reconciliation and statistical tests for gross error detection. The second part is a practical demonstration of data reconciliation on two examples. The results of reconciliation and the solution procedure are included. Complete procedure can be found in the Annex.
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Phylogeny of human populations in Papua New Guinea, a genetic and linguistic diversity hotspot
 KOPICOVÁ, Klára
A detailed phylogeny of human populations in Papua New Guinea was constructed using exhaustive topology exploration, and the fit of the model to the data was improved by adding several admixture events. The analysis relied on published genome-wide SNP genotyping data for hundreds of individuals, and qpGraph was a principal method employed in the study for testing the fit of admixture graphs to the data.
Detailed record
Data reconciliation and gross error detection
 Nováček, Adam ; Šomplák, Radovan (referee) ; Touš, Michal (advisor)
Operational data are used for control and optimization of a process in industrial and energy plants are used. Data provided from measurement are affected by errors arising from uncertainty of measurement (imprecision of measuring instruments). Data reconciliation provides us more precise variables which give us the opportunity to better optimize and achieve higher economic gains. The objective of this bachelor's thesis was to study the issue of data reconciliation of measurement and gross error detection in measurement variables. This work is divided into two parts. The first part is theoretical, describing measurement errors, solution methods for data reconciliation and statistical tests for gross error detection. The second part is a practical demonstration of data reconciliation on two examples. The results of reconciliation and the solution procedure are included. Complete procedure can be found in the Annex.
Detailed record

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