Algorithms for experimental data analysis allowing for additional a priori information

1991 ◽  
Vol 2 (2) ◽  
pp. 148-152
Author(s):  
A. I. Grebennikov
Keyword(s):  
Experimental Data ◽  
Data Analysis ◽  
A Priori ◽  
A Priori Information ◽  
Priori Information ◽  
Experimental Data Analysis

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.

scholarly journals Topological Data Analysis of Collective and Individual Epithelial Cells using Persistent Homology of Loops

Soft Matter ◽  
2021 ◽  
Author(s):  
Dhananjay Bhaskar ◽  
William Y Zhang ◽  
Ian Y Wong
Keyword(s):  
Phase Transitions ◽  
Data Analysis ◽  
Epithelial Cells ◽  
Persistent Homology ◽  
A Priori ◽  
Topological Data Analysis ◽  
A Priori Information ◽  
Priori Information ◽  
Topological Data

Interacting, self-propelled particles such as epithelial cells can dynamically self-organize into complex multicellular patterns, which are challenging to classify without \emph{a priori} information. Classically, different phases and phase transitions have...

scholarly journals A priori estimations of geometric parameters of an anomalous object in modeling the soil structure using RES3DINV software

2020 ◽  
Vol 30 (4) ◽  
pp. 696-710
Author(s):  
O.M. Nemtsova ◽  
T.M. Bannikova ◽  
V.M. Nemtsov
Keyword(s):  
Data Analysis ◽  
A Priori ◽  
Data Interpretation ◽  
Geometric Parameters ◽  
Inversion Method ◽  
A Priori Information ◽  
Input Parameters ◽  
Uniqueness Of The Solution ◽  
Ill Posed ◽  
Priori Information

We discuss the problem of proper use of software packages that implement methods for solving ill-posed problems. Most of the problems of processing experimental data belong to ill-posed problems. When using methods for solving ill-posed problems, there is a problem of non-uniqueness of the solution, which is solved by introducing a priori information. Obtaining a priori information is possible in different ways, but quantitative estimates involve the use of additional methods for data analysis. Obviously, additional methods should not be more complicated and labor intensive than the main data processing method. Using the RES3DINV electrical prospecting data analysis software as an example, the role of a priori information for obtaining reliable results is demonstrated. The RES3DINV software is used to build a soil model from the measured values of resistivity using electrical survey’s methods. When using the inversion method implemented in the software package, it is necessary to set the input parameters describing the geometric dimensions of the anomalous resistance object, which are usually unknown a priori. By model objects we demonstrate how the incorrect setting of input parameters affects the result of data interpretation. We show that the vector analysis method can be used as a way to obtain a priori information. This method allows us to obtain estimates of the geometric parameters of an anomalous object, does not involve high time and resource expenses, and can be used directly at the site of field experimental measurements.

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