scholarly journals Differences and similarities between precipitation patterns of different climates

2021 ◽  
Author(s):  
Csaba Ilyés ◽  
Valerie A. J. A. Wendo ◽  
Yetzabel Flores Carpio ◽  
Péter Szűcs
Keyword(s):  
Hydrological Cycle ◽  
Discrete Fourier Transformation ◽  
Time Interval ◽  
Mathematical Methods ◽  
Deterministic Components ◽  
Comparison Of The Results ◽  
Stochastic Time Series ◽  
Global Precipitation ◽  
Stochastic Time ◽  
Precipitation Cycles

AbstractIn recent years water-related issues are increasing globally, some researchers even argue that the global hydrological cycle is accelerating, while the number of meteorological extremities is growing. With the help of large number of available measured data, these changes can be examined with advanced mathematical methods. In the outlined research we were able to collect long precipitation datasets from two different climatical regions, one sample area being Ecuador, the other one being Kenya. Using the methodology of spectral analysis based on the discrete Fourier-transformation, several deterministic components were calculated locally in the otherwise stochastic time series, while by the comparison of the results, also with previous calculations from Hungary, several global precipitation cycles were defined in the time interval between 1980 and 2019. The results of these calculations, the described local, regional, and global precipitation cycles can be a helpful tool for groundwater management, as precipitation is the major resource of groundwater recharge, as well as with the help of these deterministic cycles, precipitation forecasts can be delivered for the areas.

scholarly journals Identification of an unstable ARMA equation

2001 ◽  
Vol 7 (1) ◽  
pp. 97-112 ◽  
Author(s):  
Yulia R. Gel ◽  
Vladimir N. Fomin
Keyword(s):  
Time Series ◽  
Least Squares ◽  
Infinite Order ◽  
Time Series Model ◽  
Identification Algorithm ◽  
Data Handling ◽  
Stochastic Time Series ◽  
Stochastic Time ◽  
Strongly Consistent ◽  
Minimal Phase

Usually the coefficients in a stochastic time series model are partially or entirely unknown when the realization of the time series is observed. Sometimes the unknown coefficients can be estimated from the realization with the required accuracy. That will eventually allow optimizing the data handling of the stochastic time series.Here it is shown that the recurrent least-squares (LS) procedure provides strongly consistent estimates for a linear autoregressive (AR) equation of infinite order obtained from a minimal phase regressive (ARMA) equation. The LS identification algorithm is accomplished by the Padé approximation used for the estimation of the unknown ARMA parameters.

Fractal and Multifractal in Stochastic Time Series

2020 ◽  
pp. 129-151
Author(s):  
Santo Banerjee ◽  
M K Hassan ◽  
Sayan Mukherjee ◽  
A Gowrisankar
Keyword(s):  
Time Series ◽  
Stochastic Time Series ◽  
Stochastic Time

scholarly journals EFFECTS OF WELDING PARAMETERS, TIME INTERVAL AND PREHEATING ON RESIDUAL STRESS AND DISTORTION OF JOINING ST52 STIFFENER RING IN AN AISI 4130 TUBULAR SHELL

2020 ◽  
Vol 3 (1) ◽  
pp. 11-15
Author(s):  
Alireza M. Haghighi ◽  
Farhad S. Samani
Keyword(s):  
Residual Stress ◽  
Welding Current ◽  
Welding Parameters ◽  
Time Interval ◽  
Negative Effects ◽  
Short Term ◽  
Welding Line ◽  
Aisi 4130 ◽  
Comparison Of The Results

Stiffener rings and stringers are used commonly in offshore and aerospace structures. Welding the stiffener to the structure causes the appearance of residual stress and distortion that leads to short-term and long-term negative effects. Residual stress and distortion of welding have destructive effects such as deformation, brittle fracture, and fatigue of the welded structures. This paper aims to investigate the effects of preheating, time interval and welding parameters such as welding current and speed on residual stress and distortion of joining an ST52-3N (DIN 1.0570) T-shape stiffener ring to an AISI 4130 (DIN 1.7218) thin-walled tubular shell by eleven pairs of welding line in both sides of the ring by means of finite element method (FEM). Results in tangent (longitudinal), axial and radial directions have been compared and the best welding methods proposed. After the comparison of the results, simultaneous welding both sides of the ring with preheating presented as the best method with less distortion and residual stresses among the studied conditions. The correctness of the FEM confirmed by the validation of the results.

A Recurrent Probabilistic Neural Network for EMG Pattern Recognition

2011 ◽  
pp. 130-153 ◽  
Author(s):  
Toshio Tsuji ◽  
Nan Bu ◽  
Osamu Fukuda
Keyword(s):  
Time Series ◽  
Pattern Recognition ◽  
Hidden Markov ◽  
Probabilistic Neural Network ◽  
Temporal Characteristic ◽  
Gaussian Mixture ◽  
Neural Computation ◽  
Emg Pattern Recognition ◽  
Stochastic Time Series ◽  
Stochastic Time

In the field of pattern recognition, probabilistic neural networks (PNNs) have been proven as an important classifier. For pattern recognition of EMG signals, the characteristics usually used are: (1) amplitude, (2) frequency, and (3) space. However, significant temporal characteristic exists in the transient and non-stationary EMG signals, which cannot be considered by traditional PNNs. In this article, a recurrent PNN, called recurrent log-linearized Gaussian mixture network (R-LLGMN), is introduced for EMG pattern recognition, with the emphasis on utilizing temporal characteristics. The structure of R-LLGMN is based on the algorithm of a hidden Markov model (HMM), which is a routinely used technique for modeling stochastic time series. Since R-LLGMN inherits advantages from both HMM and neural computation, it is expected to have higher representation ability and show better performance when dealing with time series like EMG signals. Experimental results show that R-LLGMN can achieve high discriminant accuracy in EMG pattern recognition.

scholarly journals Comparison of Methods Analyzing Bifurcation and Hunting of Complex Rail Vehicle Models

2012 ◽  
Vol 7 (4) ◽  
Author(s):  
Oldrich Polach ◽  
Ingo Kaiser
Keyword(s):  
Mechanical Design ◽  
Path Following ◽  
Time Interval ◽  
Hunting Behavior ◽  
Direct Computation ◽  
Detailed Model ◽  
Brute Force Method ◽  
Railway Passenger ◽  
The Stability ◽  
Comparison Of The Results

The stability assessment is an important task in the mechanical design of railway vehicles. For a detailed model of a railway passenger coach, the hunting behavior depending on the running speed, on wheel-rail contact conditions, and on different model configurations is analyzed using two different methods: The path-following method based on a direct computation of limit cycles enables an automatic computation. However, due to the direct computation, which exploits the periodicity of the solution, this method is restricted to strictly periodic behavior. In the brute-force method, an initial disturbance limited to a certain time interval is applied to the model. This method allows the analysis of the behavior independently from the type of the solution, but requires manual intervention. The comparison of the results obtained with both methods shows a good agreement and thereby the reliability of the results and the methods.

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