Application de la fonction bêta et des polynômes de Jacobi à l'analyse des valeurs extrêmes

1994 ◽  
Vol 21 (6) ◽  
pp. 1074-1080 ◽  
Author(s):  
J. Llamas ◽  
C. Diaz Delgado ◽  
M.-L. Lavertu
Keyword(s):  
Frequency Estimation ◽  
Probabilistic Method ◽  
Beta Function ◽  
Real Data ◽  
Flood Frequency ◽  
Data Series ◽  
Data Generation ◽  
Practical Applications ◽  
Flood Probability ◽  
Probable Maximum Flood

In this paper, an improved probabilistic method for flood analysis using the probable maximum flood, the beta function, and orthogonal Jacobi’s polynomials is proposed. The shape of the beta function depends on the sample's characteristics and the bounds of the phenomenon. On the other hand, a serial of Jacobi’s polynomials has been used improving the beta function and increasing its convergence degree toward the real flood probability density function. This mathematical model has been tested using a sample of 1000 generated beta random data. Finally, some practical applications with real data series, from important Quebec's rivers, have been performed; the model solutions for these rivers showed the accuracy of this new method in flood frequency estimation. Key words: probable maximum flood, beta function, orthogonal polynomials, distribution function, flood frequency estimation, data generation, convergency.

Guided image filtering based ℓ0 gradient minimization for limited-angle CT image reconstruction

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Tianyi Wang ◽  
Chengxiang Wang ◽  
Kequan Zhao ◽  
Wei Yu ◽  
Min Huang
Keyword(s):  
Iteration Process ◽  
Real Data ◽  
Image Filtering ◽  
Reconstruction Technique ◽  
Ct Reconstruction ◽  
Imaging Device ◽  
Practical Applications ◽  
Guided Image Filtering ◽  
Simultaneous Algebraic Reconstruction Technique ◽  
Limited Angle

Abstract Limited-angle computed tomography (CT) reconstruction problem arises in some practical applications due to restrictions in the scanning environment or CT imaging device. Some artifacts will be presented in image reconstructed by conventional analytical algorithms. Although some regularization strategies have been proposed to suppress the artifacts, such as total variation (TV) minimization, there is still distortion in some edge portions of image. Guided image filtering (GIF) has the advantage of smoothing the image as well as preserving the edge. To further improve the image quality and protect the edge of image, we propose a coupling method, that combines ℓ 0 {\ell_{0}} gradient minimization and GIF. An intermediate result obtained by ℓ 0 {\ell_{0}} gradient minimization is regarded as a guidance image of GIF, then GIF is used to filter the result reconstructed by simultaneous algebraic reconstruction technique (SART) with nonnegative constraint. It should be stressed that the guidance image is dynamically updated as the iteration process, which can transfer the edge to the filtered image. Some simulation and real data experiments are used to evaluate the proposed method. Experimental results show that our method owns some advantages in suppressing the artifacts of limited angle CT and in preserving the edge of image.

scholarly journals An Optimal Tail Selection in Risk Measurement

Risks ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 70
Author(s):  
Małgorzata Just ◽  
Krzysztof Echaust
Keyword(s):  
Mean Squared Error ◽  
Real Data ◽  
Random Variable ◽  
Threshold Level ◽  
Middle Part ◽  
Risk Measurement ◽  
Practical Applications ◽  
Tuning Parameters ◽  
Path Stability ◽  
Asymptotic Mean Squared Error

The appropriate choice of a threshold level, which separates the tails of the probability distribution of a random variable from its middle part, is considered to be a very complex and challenging task. This paper provides an empirical study on various methods of the optimal tail selection in risk measurement. The results indicate which method may be useful in practice for investors and financial and regulatory institutions. Some methods that perform well in simulation studies, based on theoretical distributions, may not perform well when real data are in use. We analyze twelve methods with different parameters for forty-eight world indices using returns from the period of 2000–Q1 2020 and four sub-periods. The research objective is to compare the methods and to identify those which can be recognized as useful in risk measurement. The results suggest that only four tail selection methods, i.e., the Path Stability algorithm, the minimization of the Asymptotic Mean Squared Error approach, the automated Eyeball method with carefully selected tuning parameters and the Hall single bootstrap procedure may be useful in practical applications.

scholarly journals Estimation of Peak Flow in Ungauged Catchments Using the Relationship between Runoff Coefficient and Curve Number

Water ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 1669 ◽  
Author(s):  
Nam Kim ◽  
Mun-Ju Shin
Keyword(s):  
Peak Flow ◽  
Curve Number ◽  
Rational Method ◽  
Runoff Coefficient ◽  
Data Generation ◽  
Ungauged Catchments ◽  
Practical Applications ◽  
Flow Estimation ◽  
Rainfall Runoff Model ◽  
The Relationship

Hourly flood flow estimation for gauged and ungauged catchments is a prerequisite for planning and water management. Various methods have been applied in a multitude of studies to calculate the peak flow for ungauged catchments. However, it is not simple for engineers to use the existing methods in practical applications. An easier method is suggested for this purpose in this study. The authors estimated the relationship between the runoff coefficient, intensity of rainfall, and curve number, and then utilized the relationship to calculated the peak flow using the rational method for ungauged catchments. Rainfall and flood time series for ungauged study catchments were generated by a simple data generation method and a distributed rainfall–runoff model. Results showed that the runoff coefficients simulated using the estimated relationship reasonably agree with the runoff coefficients in the studied ungauged catchments. In addition, the peak flow simulated using the rational method and the relationship highly agree with the peak flow in the ungauged catchments. Therefore, the peak flow in ungauged catchments can be easily calculated by this method, which is more pragmatic for engineers.

scholarly journals Microwave Dielectric Property Retrieval from Open-Ended Coaxial Probe Response with Deep Learning

2021 ◽  
Author(s):  
Cemanur Aydinalp ◽  
Sulayman Joof ◽  
Mehmet Nuri Akinci ◽  
Ibrahim Akduman ◽  
Tuba Yilmaz
Keyword(s):  
Deep Learning ◽  
Dielectric Property ◽  
Large Scale ◽  
Real Data ◽  
Learning Model ◽  
Data Generation ◽  
Retrieval Technique ◽  
Design Flexibility ◽  
A New Technique ◽  
Deep Learning Model

In the manuscript, we propose a new technique for determination of Debye parameters, representing the dielectric properties of materials, from the reflection coefficient response of open-ended coaxial probes. The method retrieves the Debye parameters using a deep learning model designed through utilization of numerically generated data. Unlike real data, using synthetically generated input and output data for training purposes provides representation of a wide variety of materials with rapid data generation. Furthermore, the proposed method provides design flexibility and can be applied to any desired probe with intended dimensions and material. Next, we experimentally verified the designed deep learning model using measured reflection coefficients when the probe was terminated with five different standard liquids, four mixtures,and a gel-like material.and compared the results with the literature. Obtained mean percent relative error was ranging from 1.21±0.06 to 10.89±0.08. Our work also presents a large-scale statistical verification of the proposed dielectric property retrieval technique.

scholarly journals SHYREG, a national database of flood frequency estimation

2016 ◽  
Vol 7 ◽  
pp. 01004
Author(s):  
Patrick Arnaud ◽  
Philippe Cantet ◽  
Jean Odry
Keyword(s):  
Frequency Estimation ◽  
Flood Frequency ◽  
National Database

scholarly journals Flood frequency estimation by continuous simulation under climate change (with uncertainty)

2000 ◽  
Vol 4 (3) ◽  
pp. 393-405 ◽  
Author(s):  
D. Cameron ◽  
K. Beven ◽  
P. Naden
Keyword(s):  
Climate Change ◽  
Frequency Estimation ◽  
Flood Frequency ◽  
Change Scenario ◽  
Rainfall Runoff ◽  
Catchment Scale ◽  
Continuous Simulation ◽  
Starting Point ◽  
Rainfall Model ◽  
Impacts Of Climate Change

Abstract. This paper explores the potential for assessing the impacts of climate change upon flood frequency for the gauged, upland Wye catchment at Plynlimon, Wales, UK, while taking account of uncertainty in modelling rainfall-runoff processes under current conditions. A continuous simulation methodology which uses a stochastic rainfall model to drive the rainfall-runoff model TOPMODEL is utilised. Behavioural parameter sets for both the rainfall model and TOPMODEL are identified prior to the climate change runs using the Generalised Likelihood Uncertainty Estimation (GLUE) methodology. The "medium-high" UKCIP98 climate change scenario, obtained from the HadCM2 GCM simulations, is used as a starting point for a variety of different scenarios at the catchment scale. It is demonstrated that while the scenarios have only a small impact upon the likelihood weighted flood frequency uncertainty bounds in comparison with the current condition scenario, the risk of a given discharge as an element in the distribution of T year floods is changed. This underlines the need to account explicitly for uncertainty within hydrological modelling, especially in estimating the impacts of climate change. Keywords: Climate change; Floods; Frequency; TOPMODEL

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