The use of a priori information in the statistical processing of experimental data

1992 ◽  
Vol 35 (9) ◽  
pp. 888-893 ◽  
Author(s):  
Yu. G. Dmitriev ◽  
P. F. Tarasenko
Keyword(s):  
Experimental Data ◽  
A Priori ◽  
Statistical Processing ◽  
A Priori Information ◽  
Priori Information

scholarly journals Production Possibility Frontiers and Estimation of Competition Effects: The Use of A Priori Information on Biological Processes in Intercropping

1992 ◽  
Vol 28 (3) ◽  
pp. 351-368 ◽  
Author(s):  
Radha Ranganathan
Keyword(s):  
Experimental Data ◽  
Biomass Yield ◽  
Plant Density ◽  
A Priori ◽  
Biological Processes ◽  
A Priori Information ◽  
Production Frontier ◽  
Production Possibility ◽  
Competition Effects ◽  
Priori Information

SummaryProduction possibility frontiers contribute much to an economic evaluation of yield advantages from intercropping. The difficulty with estimating a production frontier empirically from experimental data is one of ascertaining that the fitted curve corresponds with the frontier. This problem has been overcome by deriving the frontier from a priori knowledge of the biological processes that determine the outcome in intercropping. The hyperbolic relationship between biomass yield and plant density, and the parameters that characterize the degree of intra-and inter-specific competition in intercropping are used in this paper to derive production possibility frontiers. The method is illustrated with data from three intercropping studies. A brief review of the two main methods used by researchers to evaluate the results of intercropping, and their limitations, is also presented.

scholarly journals Estimation of performance parameters of turbine engine components using experimental data in parametric uncertainty conditions

2019 ◽  
Vol 304 ◽  
pp. 03003
Author(s):  
Olexandr Khustochka ◽  
Sergey Chernysh ◽  
Sergiy Yepifanov ◽  
Mykhaylo Ugryumov ◽  
Radoslaw Przysowa
Keyword(s):  
Experimental Data ◽  
Path Analysis ◽  
Measurement Errors ◽  
A Priori ◽  
Parametric Uncertainty ◽  
Performance Parameters ◽  
A Priori Information ◽  
Turbine Engine ◽  
Priori Information ◽  
Engine Components

Gas Path Analysis and matching turbine engine models to experimental data are inverse problems of mathematical modelling which are characterized by parametric uncertainty. It results from the fact that the number of measured parameters is significantly less than the number of components’ performance parameters needed to describe the real engine. Inthese conditions, even small measurement errors can result in a high variation of results, and obtained efficiency, lossfactors etc. can appear out of the physical range. The paper presents new method for setting a priori information about the engine and its performance in view of fuzzy sets, forming objective functions and scalar convolutions synthesis of these functions to estimate gas-path components’ parameters. The comparison of the proposed approach with traditional methods showed that its main advantage is high stability of estimation in the parametric uncertainty conditions. It reduces scattering, excludes incorrect solutions which do not correspond to a priori assumptions, and also helps to implement the Gas Path Analysis at the limited number of measured parameters.

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