scholarly journals Assessment of GNSS Orthogonal Transformation Model

2012 ◽  
Vol 65 (3) ◽  
pp. 561-570 ◽  
Author(s):  
Wantong Chen ◽  
Yanzhong Zhang
Keyword(s):  
Orthogonal Transformation ◽  
Transformation Method ◽  
Transformation Model ◽  
Integer Ambiguity ◽  
Baseline Model ◽  
Short Baseline ◽  
Conditional Least Squares ◽  
Important Field ◽  
Positioning Technique ◽  
The Mathematical Model

GNSS relative positioning technique is an important field of study, in which the standard ‘GNSS Baseline Model’ is often used. Differencing between observation equations is used to construct the mathematical model, since this method can eliminate some common errors in the GNSS signal measurements. The ‘Orthogonal Transformation’ method can also construct the GNSS Baseline Model. However, as is described by some scholars, this model may avoid some drawbacks of Double Differencing (DD) while maintaining all the advantages. For comparison purposes, this model is evaluated and the theoretical equivalence of both approaches is proved for the short baseline from two aspects: the Integer Ambiguity Resolution and the conditional least-squares baseline vector.

Bootstrap LM Tests for Spatial Dependence in Panel Data Models with Fixed Effects

2019 ◽  
Vol 7 (4) ◽  
pp. 330-343
Author(s):  
Bianling Ou ◽  
Zhihe Long ◽  
Wenqian Li
Keyword(s):  
Panel Data ◽  
Spatial Dependence ◽  
Fixed Effects ◽  
Orthogonal Transformation ◽  
Transformation Method ◽  
Data Models ◽  
Panel Data Models ◽  
Significance Level ◽  
Lm Tests ◽  
Nominal Significance

Abstract This paper applies bootstrap methods to LM tests (including LM-lag test and LM-error test) for spatial dependence in panel data models with fixed effects, and removes fixed effects based on orthogonal transformation method proposed by Lee and Yu (2010). The consistencies of LM tests and their bootstrap versions are proved, and then some asymptotic refinements of bootstrap LM tests are obtained. It shows that the convergence rate of bootstrap LM tests is O((NT)−2) and that of fast double bootstrap LM tests is O((NT)−5/2). Extensive Monte Carlo experiments suggest that, compared to aysmptotic LM tests, the size of bootstrap LM tests gets closer to the nominal level of signifiance, and the power of bootstrap LM tests is higher, especially in the cases with small spatial correlation. Moreover, when the error is not normal or with heteroskedastic, asymptotic LM tests suffer from severe size distortion, but the size of bootstrap LM tests is close to the nominal significance level. Bootstrap LM tests are superior to aysmptotic LM tests in terms of size and power.

scholarly journals Statistical Methods for Predicting Malaria Incidences Using Data from Sudan

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Hamid H. Hussien ◽  
Fathy H. Eissa ◽  
Khidir E. Awadalla
Keyword(s):  
Time Series ◽  
Malaria Incidence ◽  
Moving Average ◽  
Forecast Accuracy ◽  
Transformation Method ◽  
Transformation Model ◽  
Future Research ◽  
Incidence Data ◽  
Moving Average Model ◽  
Using Data

Malaria is the leading cause of illness and death in Sudan. The entire population is at risk of malaria epidemics with a very high burden on government and population. The usefulness of forecasting methods in predicting the number of future incidences is needed to motivate the development of a system that can predict future incidences. The objective of this paper is to develop applicable and understood time series models and to find out what method can provide better performance to predict future incidences level. We used monthly incidence data collected from five states in Sudan with unstable malaria transmission. We test four methods of the forecast: (1) autoregressive integrated moving average (ARIMA); (2) exponential smoothing; (3) transformation model; and (4) moving average. The result showed that transformation method performed significantly better than the other methods for Gadaref, Gazira, North Kordofan, and Northern, while the moving average model performed significantly better for Khartoum. Future research should combine a number of different and dissimilar methods of time series to improve forecast accuracy with the ultimate aim of developing a simple and useful model for producing reasonably reliable forecasts of the malaria incidence in the study area.

Research and Application on Fracturing Fluid Loss Model for Glutenite Formation

2013 ◽  
Vol 295-298 ◽  
pp. 2842-2847
Author(s):  
Yong Ming Li ◽  
Pan Luo ◽  
Jin Zhou Zhao ◽  
Ya Zhou Li
Keyword(s):  
Filtration Rate ◽  
Orthogonal Transformation ◽  
Transformation Method ◽  
Fluid Loss ◽  
Natural Fractures ◽  
Matrix Permeability ◽  
Fracturing Fluids ◽  
Gravel Size ◽  
Dual Porosity Model ◽  
Porosity Model

Gravels and natural fractures in glutenite formation have significant impacts on fluid loss when hydraulic fracturing is conducted. Matrix permeability and porosity were computed through Kozeny-Carman equation when gravels contents and size are known. Then a pebbly dual permeability dual porosity model was used to quantitatively evaluate the fracturing fluids loss in glutenite formation. Filtration rate curves could be plotted from the pressure distribution function which was obtained through orthogonal transformation method. Different gravels contents and multi-size-gravels were taken into accounts in this paper. The results show that both filtration rates in matrix and natural fractures decrease with increasing gravels content in matrix; and the filtration rate in matrix decrease much more. Impacts of gravel content are more significant than impacts of gravel size. Natural fractures have much more significant impacts than gravels.

scholarly journals The Solution of a Mathematical Model for Dengue Fever Transmission Using Differential Transformation Method

2019 ◽  
pp. 82-87
Author(s):  
Felix Yakubu Eguda ◽  
Andrawus James ◽  
Sunday Babuba
Keyword(s):  
Mathematical Model ◽  
Dengue Fever ◽  
Transformation Method ◽  
Vital Role ◽  
Differential Transformation Method ◽  
Linear Ordinary Differential Equations ◽  
Differential Transformation ◽  
Long Term Behavior ◽  
The Mathematical Model

Differential Transformation Method (DTM) is a very effective tool for solving linear and non-linear ordinary differential equations. This paper uses DTM to solve the mathematical model for the dynamics of Dengue fever in a population. The graphical profiles for human population are obtained using Maple software. The solution profiles give the long term behavior of Dengue fever model which shows that treatment plays a vital role in reducing the disease burden in a population.

scholarly journals Improvement of Multi-GNSS Precision and Success Rate Using Realistic Stochastic Model of Observations

2021 ◽  
Vol 14 (1) ◽  
pp. 60
Author(s):  
Farinaz Mirmohammadian ◽  
Jamal Asgari ◽  
Sandra Verhagen ◽  
Alireza Amiri-Simkooei
Keyword(s):  
Stochastic Model ◽  
Data Processing ◽  
Success Rate ◽  
Global Navigation Satellite Systems ◽  
Integer Ambiguity ◽  
Double Difference ◽  
Unbiased Estimation ◽  
Data Sets ◽  
Short Baseline ◽  
Gnss Data

With the advancement of multi-constellation and multi-frequency global navigation satellite systems (GNSSs), more observations are available for high precision positioning applications. Although there is a lot of progress in the GNSS world, achieving realistic precision of the solution (neither too optimistic nor too pessimistic) is still an open problem. Weighting among different GNSS systems requires a realistic stochastic model for all observations to achieve the best linear unbiased estimation (BLUE) of unknown parameters in multi-GNSS data processing mode. In addition, the correct integer ambiguity resolution (IAR) becomes crucial in shortening the Time-To-Fix (TTF) in RTK, especially in challenging environmental conditions. In general, it is required to estimate various variances for observation types, consider the correlation between different observables, and compensate for the satellite elevation dependence of the observable precision. Quality control of GNSS signals, such as GPS, GLONASS, Galileo, and BeiDou can be performed by processing a zero or short baseline double difference pseudorange and carrier phase observations using the least-squares variance component estimation (LS-VCE). The efficacy of this method is investigated using real multi-GNSS data sets collected by the Trimble NETR9, SEPT POLARX5, and LEICA GR30 receivers. The results show that the standard deviation of observations depends on the system and the observable type in which a particular receiver could have the best performance. We also note that the estimated variances and correlations among different observations are also dependent on the receiver type. It is because the approaches utilized for the recovery techniques differ from one type of receiver to another kind. The reliability of IAR will improve if a realistic stochastic model is applied in single or multi-GNSS data processing. According to the results, for the data sets considered, a realistic stochastic model can increase the computed empirical success rate to 100% in multi-GNSS as well as a single system. As mentioned previously, the realistic precision of the solution can be achieved with a realistic stochastic model. However, using the estimated stochastic model, in fact, leads to better precision and accuracy for the estimated baseline components, up to 39% in multi-GNSS.

scholarly journals Dynamical Analysis of Corona-virus (COVID−19) Epidemic Model by Differential Transform Method

2020 ◽  
Author(s):  
A. John Christopher ◽  
N. Magesh ◽  
G. Tamil Preethi
Keyword(s):  
Mathematical Model ◽  
Preventive Measures ◽  
Control Strategies ◽  
Transformation Method ◽  
Dynamical Analysis ◽  
Transform Method ◽  
Potential Control ◽  
Corona Virus ◽  
Differential Transform ◽  
The Mathematical Model

Abstract The aim of this paper is applying the Differential Transformation Method (DTM) to analyze and find the solution for the mathematical model described by the system of nonlinear ordinary differential equations which describe the epidemiology of the most threatening virus called Corona-virus later labelled as COVID-19. The behaviour of the outcomes is presented in terms of plots. Finally, the present study may help you to examine the wild class of real world models and also aid to predict their behaviour with respect to parameters considered in the model. The purpose of this study is to estimate the effectiveness of preventive measures, predicting future outbreaks and potential control strategies using the mathematical model.

Acoustic waves in two-fraction mixtures of liquid with vapor-gas bubbles

2012 ◽  
Vol 9 (1) ◽  
pp. 65-68
Author(s):  
R.N. Gafiyatov
Keyword(s):  
Acoustic Waves ◽  
Gas Bubbles ◽  
Transformation Method ◽  
Fast Fourier Transformation ◽  
Fourier Transformation Method ◽  
Impulse Pressure ◽  
Pressure Perturbations ◽  
The Mathematical Model ◽  
Different Gases ◽  
Fractional Mixture

The mathematical model of two-fractional mixture of liquid with vapor-gas bubbles of different gases and sizes with phase transformations is presented. The dispersive equation is received, dispersive curves that determine the propagation of acoustic disturbances was plotted. Calculations on the propagation of impulse pressure perturbations were performed by means of a fast Fourier transformation method.

scholarly journals Detection and elimination method for deception jamming based on an antenna array

2018 ◽  
Vol 14 (5) ◽  
pp. 155014771877446 ◽  
Author(s):  
Shuyan Ni ◽  
Jianhua Cui ◽  
Naiping Cheng ◽  
Yurong Liao
Keyword(s):  
Global Positioning System ◽  
Measurement Errors ◽  
Integer Ambiguity ◽  
Double Difference ◽  
Fast Method ◽  
Short Baseline ◽  
Elimination Method ◽  
Medium Length ◽  
Global Positioning ◽  
Jamming Detection

A global positioning system is an important way of locating an aircraft, while deception jamming can affect the positioning accuracy of such navigation. Considering this, a detection and elimination method for deception jamming is proposed based on a specially designed array for the aircraft. The jamming is detected by comparing the double-difference observation of the carrier phases of two different signals to a certain threshold derived according to the measurement errors of the receiver. To estimate the jamming direction with high accuracy, meanwhile considering the feasibility of airborne installation, a novel configurated array combining medium-length baseline with short baseline is designed, and a fast method to solve the integer ambiguity is discussed. After jamming detection, the nulling of the array beam is pointed to the jamming source through the orthogonal vector weighting to suppress jamming. The validity of the method is verified by computer simulations.

Sign in / Sign up

Export Citation Format

Share Document