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 Showing 201 - 400 of 538 Journals sorted alphabetically Educação Matemática Debate Edumatica : Jurnal Pendidikan Matematika EduMatSains Electronic Journal of Differential Equations Electronic Journal of Graph Theory and Applications       (Followers: 3) Em Teia : Revista de Educação Matemática e Tecnológica Iberoamericana Emergent Scientist Energy for Sustainable Development       (Followers: 13) Enseñanza de las Ciencias : Revista de Investigación y Experiencias Didácticas Entropy       (Followers: 5) ESAIM: Control Optimisation and Calculus of Variations       (Followers: 2) Euclid European Journal of Applied Mathematics European Journal of Combinatorics       (Followers: 3) European Journal of Mathematics       (Followers: 1) European Scientific Journal       (Followers: 1) Examples and Counterexamples Experimental Mathematics       (Followers: 5) Expositiones Mathematicae       (Followers: 2) Extracta Mathematicae Facta Universitatis, Series : Mathematics and Informatics Finite Fields and Their Applications       (Followers: 5) Fixed Point Theory and Applications Formalized Mathematics Forum of Mathematics, Pi       (Followers: 1) Forum of Mathematics, Sigma       (Followers: 1) Foundations and Trends® in Econometrics       (Followers: 6) Foundations and Trends® in Networking       (Followers: 1) Foundations and Trends® in Stochastic Systems       (Followers: 1) Foundations and Trends® in Theoretical Computer Science       (Followers: 1) Foundations of Computational Mathematics Fractal and Fractional Fractals       (Followers: 1) Frontiers of Mathematics in China Fuel Cells Bulletin       (Followers: 9) Functional Analysis and Other Mathematics       (Followers: 4) Fundamental Journal of Mathematics and Applications Funktsional'nyi Analiz i ego Prilozheniya Fuzzy Optimization and Decision Making       (Followers: 8) Game Theory       (Followers: 2) Games       (Followers: 4) Games and Economic Behavior       (Followers: 25) Gamm - 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Non-Destructive Testing and Condition Monitoring       (Followers: 110) International Electronic Journal of Algebra International Journal for Numerical Methods in Engineering       (Followers: 35) International Journal for Numerical Methods in Fluids       (Followers: 19) International Journal of Advanced Mathematical Sciences International Journal of Advanced Mechatronic Systems       (Followers: 2) International Journal of Advanced Research in Mathematics International Journal of Advances in Engineering Sciences and Applied Mathematics       (Followers: 10) International Journal of Algebra and Computation       (Followers: 1) International Journal of Algebra and Statistics       (Followers: 3) International Journal of Applied and Computational Mathematics International Journal of Applied Mathematical Research       (Followers: 1) International Journal of Applied Mathematics and Computer Science       (Followers: 7) International Journal of Applied Mechanics       (Followers: 8) International Journal of Applied Nonlinear Science International Journal of Autonomic Computing       (Followers: 1) International Journal of Bifurcation and Chaos       (Followers: 4) International Journal of Biomathematics       (Followers: 2) International Journal of Computational Complexity and Intelligent Algorithms International Journal of Computational Economics and Econometrics       (Followers: 6) International Journal of Computational Geometry and Applications       (Followers: 2) International Journal of Computational Intelligence and Applications       (Followers: 2) International Journal of Computational Methods       (Followers: 4) International Journal of Computer Processing Of Languages       (Followers: 1) International Journal of Control, Automation and Systems       (Followers: 15) International Journal of Dynamical Systems and Differential Equations       (Followers: 1) International Journal of Economics and Accounting       (Followers: 1) International Journal of Foundations of Computer Science       (Followers: 3) International Journal of Fuzzy Computation and Modelling       (Followers: 2) International Journal of Image and Graphics       (Followers: 5) International Journal of Industrial Electronics and Drives       (Followers: 3) International Journal of Low-Carbon Technologies       (Followers: 1) International Journal of Mathematical Education in Science and Technology       (Followers: 9) International Journal of Mathematical Modelling & Computations       (Followers: 3) International Journal of Mathematical Modelling and Numerical Optimisation       (Followers: 5) International Journal of Mathematical Sciences and Computing International Journal of Mathematics       (Followers: 4) International Journal of Mathematics & Computation International Journal of Mathematics and Mathematical Sciences       (Followers: 4) International Journal of Mathematics in Operational Research       (Followers: 2) International Journal of Metaheuristics       (Followers: 1) International Journal of Modelling in Operations Management       (Followers: 2) International Journal of Modern Nonlinear Theory and Application       (Followers: 1) International Journal of Number Theory       (Followers: 1) International Journal of Partial Differential Equations       (Followers: 2) International Journal of Polymer Science       (Followers: 25) International Journal of Pure Mathematical Sciences International Journal of Reliability, Quality and Safety Engineering       (Followers: 14) International Journal of Research in Undergraduate Mathematics Education       (Followers: 4) International Journal of Sediment Research       (Followers: 2) International Journal of Shape Modeling       (Followers: 1) International Journal of Theoretical and Mathematical Physics       (Followers: 13) International Journal of Trends in Mathematics Education Research       (Followers: 4) International Journal of Ultra Wideband Communications and Systems International Journal of Wavelets, Multiresolution and Information Processing International Journal on Artificial Intelligence Tools       (Followers: 9) International Mathematics Research Notices       (Followers: 1) Internet Mathematics       (Followers: 1) Inventiones mathematicae       (Followers: 2) Inverse Problems in Science and Engineering       (Followers: 3) Investigations in Mathematics Learning Iranian Journal of Optimization       (Followers: 2) Israel Journal of Mathematics Ithaca : Viaggio nella Scienza ITM Web of Conferences Izvestiya Rossiiskoi Akademii Nauk. Seriya Matematicheskaya Jahresbericht der Deutschen Mathematiker-Vereinigung Japan Journal of Industrial and Applied Mathematics Japanese Journal of Mathematics JIPM (Jurnal Ilmiah Pendidikan Matematika) JMPM : Jurnal Matematika dan Pendidikan Matematika JOHME : Journal of Holistic Mathematics Education       (Followers: 3) Johnson Matthey Technology Review Jornal Internacional de Estudos em Educação Matemática Journal d'Analyse Mathématique       (Followers: 2) Journal de Mathématiques Pures et Appliquées       (Followers: 3) Journal for Research in Mathematics Education       (Followers: 29) Journal für Mathematik-Didaktik Journal of Advanced Mathematics and Applications       (Followers: 1) Journal of Algebra       (Followers: 3) Journal of Algebra and Its Applications       (Followers: 3) Journal of Algebraic Combinatorics       (Followers: 3) Journal of Algorithms & Computational Technology Journal of Applied Mathematics       (Followers: 3) Journal of Applied Mathematics and Computing Journal of Applied Mathematics, Statistics and Informatics       (Followers: 1) Journal of Artificial Intelligence and Data Mining       (Followers: 10) Journal of Classification       (Followers: 5) Journal of Combinatorial Designs       (Followers: 4) Journal of Combinatorial Optimization       (Followers: 7) Journal of Combinatorial Theory, Series A       (Followers: 5) Journal of Combinatorial Theory, Series B       (Followers: 3) Journal of Complex Analysis       (Followers: 2) Journal of Complex Networks       (Followers: 1) Journal of Complexity       (Followers: 6) Journal of Computational and Applied Mathematics       (Followers: 6) Journal of Computational Biology       (Followers: 9) Journal of Computational Mathematics and Data Science Journal of Computational Multiphase Flows       (Followers: 1) Journal of Computational Physics       (Followers: 59) Journal of Computational Physics : X       (Followers: 1) Journal of Computer Engineering, System and Science (CESS) Journal of Contemporary Mathematical Analysis Journal of Cryptology       (Followers: 5) Journal of Difference Equations and Applications Journal of Differential Equations       (Followers: 1) Journal of Discrete Mathematics       (Followers: 1) Journal of Dynamics and Differential Equations Journal of Engineering Mathematics       (Followers: 2) Journal of Evolution Equations Journal of Experimental Algorithmics Journal of Flood Risk Management       (Followers: 14) Journal of Function Spaces Journal of Functional Analysis       (Followers: 3) Journal of Geochemical Exploration       (Followers: 4) Journal of Geological Research       (Followers: 1) Journal of Geovisualization and Spatial Analysis Journal of Global Optimization       (Followers: 6) Journal of Global Research in Mathematical Archives Journal of Homotopy and Related Structures Journal of Honai Math Journal of Humanistic Mathematics       (Followers: 1) Journal of Hyperbolic Differential Equations Journal of Indian Council of Philosophical Research Journal of Industrial Mathematics       (Followers: 2) Journal of Inequalities and Applications Journal of Infrared, Millimeter and Terahertz Waves       (Followers: 3) Journal of Integrable Systems Journal of Knot Theory and Its Ramifications       (Followers: 2) Journal of Liquid Chromatography & Related Technologies       (Followers: 7) Journal of Logical and Algebraic Methods in Programming       (Followers: 1) Journal of Manufacturing Systems       (Followers: 3) Journal of Mathematical Analysis and Applications       (Followers: 3) Journal of mathematical and computational science       (Followers: 2)

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Similar Journals
 International Journal of Advances in Engineering Sciences and Applied MathematicsNumber of Followers: 10      Hybrid journal (It can contain Open Access articles) ISSN (Print) 0975-0770 - ISSN (Online) 0975-5616 Published by Springer-Verlag  [2469 journals]
• On first-come, first-served queues with three classes of impatient
customers

Abstract: Abstract In this article, we study queuing systems with three classes of impatient customers which differ across the classes in their distribution of service times and patience times. The customers are served on a first-come, first-served (FCFS) policy independent of their classes. Such systems are common in customer call centers, which often segment their arrivals into classes of callers whose requests differ in complexity and criticality. First of all, we consider an $$M/G/1 + M$$ queue and then analyze the $$M/M/m + M$$ system. Using the virtual waiting time process, we obtain performance measures such as the percentage of customers receiving service in each class, the expected waiting times of customers in each class, and the average number of customers waiting in the queue. We use our characterization to perform a numerical analysis of the $$M/M/m + M$$ system. Finally, we compare the performance of a system based on numerical solution with the steady-state performance measures of a comparable $$M/M/m + M$$ system.
PubDate: 2022-03-01
DOI: 10.1007/s12572-022-00313-4

• The covariation-based Yule–Walker method for multidimensional
autoregressive time series with $$\alpha$$ α -stable distributed noise

Abstract: Abstract In this paper, we consider the vector autoregressive time series with multidimensional $$\alpha$$ -stable noise where $$1<\alpha <2$$ . This model takes into account the short-term dependence in the multidimensional data and possible large observations (outliers). However, for the processes based on the $$\alpha$$ -stable distribution, the classical dependence measures known as the covariance function or the correlation function are not defined due to the diverging second moment. And therefore, the classical estimation method related to the covariance-based Yule–Walker (Y-W) equations should not be used in this case. Here, we propose to generalize the Y-W equations by replacing the covariance function with the covariation function which is a properly defined dependence measure for the symmetric $$\alpha$$ -stable distribution. Based on the covariation-based Yule–Walker equations, we propose a new estimation method and we demonstrate its efficiency by conducting a simulation study on the trajectories of two- and three-dimensional $$\alpha$$ -stable VAR(1) time series. Moreover, we compare the new covariation-based technique with the classical Yule–Walker method based on the covariance function. We emphasize that the estimation technique introduced in this paper extends the generalized Yule–Walker method introduced by Gallagher (Stat Prob Lett 53:381–390, 2001) for one-dimensional $$\alpha$$ -stable autoregressive models. The theoretical results are illustrated by the real data analysis of a bivariate data set describing the daily prices of KGHM and copper.
PubDate: 2022-02-23
DOI: 10.1007/s12572-022-00315-2

• A stabilized local projection finite element scheme for computations of
oldroyd-B viscoelastic fluid flows

Abstract: Abstract This paper presents the numerical analysis of the three-field stabilized formulation based on the one-level local projection stabilization (LPS) for computations of the coupled Navier-Stokes and Oldroyd-B viscoelastic constitutive equations. Due to dominating convective terms, the velocity-pressure-stress formulation suffers from numerical instability in viscoelastic flows. The other challenges are the necessity of the inf-sup conditions for the velocity-pressure and stress-velocity couplings in equal-order interpolations. One-level local projection stabilization scheme allows us to use equal-order interpolation spaces for the velocity and the viscoelastic stress, whereas inf-sup stable finite elements are used for the velocity and the pressure approximations. The local projection method is based on a projection $$\pi _h: V_h \rightarrow D_h$$ of finite element approximation space $$V_h$$ into a discontinuous space $$D_h$$ . In one-level LPS, the approximation and projection spaces are defined on the same mesh, with an enriched approximation space. We prove the stability and a priori error analysis, ensuring the optimal order of convergence of the proposed numerical scheme. The numerical result validates the theoretical estimates.
PubDate: 2022-02-18
DOI: 10.1007/s12572-022-00314-3

• Semi-analytical framework for stress–conductivity correlations in
periodic granular assemblies under compaction

Abstract: Abstract The contact network, defined by a fabric tensor, influences phenomena such as force or heat transfer in a granular assembly. The correlation between fabric, stress, and conductivity has, however, been least explored. Furthermore, a link between these quantities may help to build a benchmark method to assist experiments substantially. The present work bridges the gap between the macroscopic quantities, such as stress and conductivity tensor, using its microscopic connection and the fabric tensor. The study presents a few interesting functional forms and non-dimensional macroscopic quantities that couple conductivity, stress, and fabric. The main feature of these functional forms is that they are independent of friction. These functional forms will provide a good estimate of fabric and conductivity which can be used real-time during the experimental investigations as well.
PubDate: 2021-12-01
DOI: 10.1007/s12572-021-00294-w

• Fatigue life prediction in nickel-based superalloys using unified
mechanics theory

Abstract: Abstract Under strain-controlled cyclic loading at elevated temperature (650 °C), the low-cycle fatigue behavior of an advanced nickel-based superalloy (RR1000) has been studied. In the current study, a unified mechanics theory (UMT)-based model is presented and applied to predict the fatigue life of nickel-based superalloy (RR1000). Entropy is used as a damage metric in the fatigue life prediction of material in the present study. The entropy generation rate under the mechanical loading conditions is calculated by considering plastic deformation as the governing mechanism for dissipation. Using the UMT, damage in nickel-based superalloy (RR1000) is evaluated to predict low-cycle fatigue life. Also, the stress–strain hysteresis loop prediction has been done at any strain amplitude without making use of curve-fitting phenomenological models. The hysteresis loops can be predicted at any given number of cycles for all strain amplitudes using UMT without doing complete fatigue experiments, which in turn reduces the efforts and costs of the cumbersome fatigue experiments.
PubDate: 2021-11-18
DOI: 10.1007/s12572-021-00296-8

• Preface to special issue: time series modelling

PubDate: 2021-09-01
DOI: 10.1007/s12572-021-00310-z

• Asymptotic behavior of dependence measures for Ornstein-Uhlenbeck model
based on long memory processes

Abstract: Abstract In this paper, we study the long memory property of two processes based on the Ornstein-Uhlenbeck model. Their are extensions of the Ornstein-Uhlenbeck system for which in the classic version we replace the standard Brownian motion (or other L $$\acute{e}$$ vy process) by long range dependent processes based on $$\alpha -$$ stable distribution. One way of characterizing long- and short-range dependence of second order processes is in terms of autocovariance function. However, for systems with infinite variance the classic measure is not defined, therefore there is a need to consider alternative measures on the basis of which the long range dependence can be recognized. In this paper, we study three alternative measures adequate for $$\alpha -$$ stable-based processes. We calculate them for examined processes and indicate their asymptotic behavior. We show that one of the analyzed Ornstein-Uhlenbeck process exhibits long memory property while the second does not. Moreover, we show the ratio of two introduced measures is limited which can be a starting point to introduction of a new estimation method of stability index for analyzed Ornstein-Uhlenbeck processes.
PubDate: 2021-09-01
DOI: 10.1007/s12572-021-00305-w

• Time series forecasting: problem of heavy-tailed distributed noise

Abstract: Abstract Time series forecasting has been the area of intensive research for years. Statistical, machine learning or mixed approaches have been proposed to handle this one of the most challenging tasks. However, little research has been devoted to tackle the frequently appearing assumption of normality of given data. In our research, we aim to extend the time series forecasting models for heavy-tailed distribution of noise. In this paper, we focused on normal and Student’s t distributed time series. The SARIMAX model (with maximum likelihood approach) is compared with the regression tree-based method—random forest. The research covers not only forecasts but also prediction intervals, which often have hugely informative value as far as practical applications are concerned. Although our study is focused on the selected models, the presented problem is universal and the proposed approach can be discussed in the context of other systems.
PubDate: 2021-09-01
DOI: 10.1007/s12572-021-00312-x

• Normal inverse Gaussian autoregressive model using EM algorithm

Abstract: Abstract In this article, normal inverse Gaussian (NIG) autoregressive model is introduced. The parameters of the model are estimated using expectation maximization (EM) algorithm. The efficacy of the EM algorithm is shown using simulated and real-world financial data. It is shown that NIG autoregressive model fit very well on the considered financial data and hence could be useful in modelling of various real-life time-series data.
PubDate: 2021-09-01
DOI: 10.1007/s12572-021-00303-y

• Estimating stress-strength reliability for exponential distributions with
different location and scale parameters

Abstract: Abstract The paper deals with estimating the stress-strength reliability of a system where the stress and strength random variables follow two-parameter exponential distributions with different location and scale parameters assuming all parameters are unknown. We derive the maximum likelihood estimator, uniformly minimum variance unbiased estimator, and Bayes estimator of the stress-strength reliability. Confidence intervals based on the generalised variable method and bootstrap methods are proposed. We conduct a comprehensive simulation study to compare the estimators of the reliability functions.
PubDate: 2021-09-01
DOI: 10.1007/s12572-021-00308-7

• Fractional lower-order covariance (FLOC)-based estimation for
multidimensional PAR(1) model with $$\alpha -$$ α - stable noise

Abstract: Abstract Many real data exhibit periodic behavior. The periodic autoregressive moving average (PARMA) is one of the most common and useful model to describe these data. In the classical case, the PARMA model is considered by the assumption of Gaussian (or finite-variance) distribution of the noise. However, the Gaussian distribution seems to be unsuitable in many real applications, especially when the corresponding data exhibit impulsive-like behavior. Therefore, the extensions of the classical PARMA models are considered and the Gaussian distribution of the noise is replaced by the so-called heavy-tailed distribution. One of the most known distribution that can be used here is the $$\alpha -$$ stable one. In this paper, we introduce a new estimation technique for the parameters of the multidimensional periodic autoregressive time series of order 1 (i.e., PAR(1)), which is based on fractional lower-order covariance, the alternative dependence measure adequate for $$\alpha -$$ stable distributed models. From theoretical point of view, the use of this technique is justified as in this case the classical measure (i.e., covariance) is not defined. The practical aspect of this technique is discussed. The efficiency of the technique on simulated data is demonstrated using the Monte Carlo approach in different contexts, including the sample size and index of stability $$\alpha$$ of the noise’s distribution. Lastly, we present the real data analysis.
PubDate: 2021-09-01
DOI: 10.1007/s12572-021-00301-0

• Fractional differentiation and its use in machine learning

Abstract: Abstract This article covers the implementation of fractional (non-integer order) differentiation on real data of four datasets based on stock prices of main international stock indexes: WIG 20, S&P 500, DAX and Nikkei 225. This concept has been proposed by Lopez de Prado [5] to find the most appropriate balance between zero differentiation and fully differentiated time series. The aim is making time series stationary while keeping its memory and predictive power. In addition, this paper compares fractional and classical differentiation in terms of the effectiveness of artificial neural networks. Root mean square error (RMSE) and mean absolute error (MAE) are employed in this comparison. Our investigations have determined the conclusion that fractional differentiation plays an important role and leads to more accurate predictions in case of ANN.
PubDate: 2021-09-01
DOI: 10.1007/s12572-021-00299-5

• On the choice of hyper-parameters of artificial neural networks for
stabilized finite element schemes

Abstract: Abstract This paper provides guidelines for an effective artificial neural networks (ANNs) design to aid stabilized finite element schemes. In particular, ANNs are used to estimate the stabilization parameter of the streamline upwind Petrov–Galerkin (SUPG) stabilization scheme for singularly perturbed problems. The effect of the artificial neural network (ANN) hyper-parameters on the accuracy of ANNs is found by performing a global sensitivity analysis. First, a Gaussian process regression metamodel of the artificial neural networks is obtained. Next, analysis of variance is performed to obtain Sobol’ indices. The total-order Sobol’ indices identify the hyper-parameters having the maximum effect on the accuracy of the ANNs. Furthermore, the best-performing and the worst-performing networks are identified among the candidate ANNs. Our findings are validated with the help of one-dimensional test cases in the advection-dominated flow regime. This study provides insights into hyper-parameters’ effect and consequently aids in building effective ANN models for applications involving nonlinear regression, including estimation of SUPG stabilization parameters.
PubDate: 2021-09-01
DOI: 10.1007/s12572-021-00306-9

• Asymptotic performance of the Scheduled Relaxation Jacobi method

Abstract: Abstract The performance of the Scheduled Relaxation Jacobi method for levels as high as 25 and mesh size as large as $$4096\times 4096$$ is studied in the present work. The optimal values for the relaxation parameters have been obtained using a search procedure proposed in an earlier study by the same author after suitable modifications and improvements which allow it to be used for the present purpose. It is shown that for a given number of levels and mesh size, the theoretical spectral radius and the speed-up of the method improve as the upper limit for the value of the relaxation factor is increased, albeit at the cost of numerical stability. Since the values for the over-relaxation factors for the cases considered here are high and there are more than one under-relaxation factor, a proper sequencing of the over- and under-relaxed iterations is essential and a strategy for the same is proposed. The five level method with suitably determined optimal values is shown to perform better than a twenty five level method, when used for solving the Neumann–Laplace problem, despite the theoretical spectral radius of the former being less than that of the latter. The numerical calculations demonstrate that the SRJ method with optimal parameters can achieve a reduction in the initial error by four orders of magnitude within 3000 iterations even for a 4096 $$\times$$ 4096 mesh.
PubDate: 2021-09-01
DOI: 10.1007/s12572-021-00297-7

• Spatial components dependence for bidimensional time-constant AR(1) model
with $$\alpha$$ α -stable noise and triangular coefficients matrix

Abstract: Abstract In this paper, we examine the bidimensional time-constant autoregressive model of order 1 with $$\alpha$$ -stable noise. We focus on the case of the triangular coefficients matrix for which one of the spatial components of the model simplifies to the one-dimensional autoregressive time series. We study the asymptotic behaviour of the cross-codifference and the cross-covariation applied to describe the dependence in time between the spatial components of the model. As a result, we formulate the theorem about the asymptotic relation between both measures, which is consistent with the result that is correct for the case of the non-triangular coefficients matrix.
PubDate: 2021-09-01
DOI: 10.1007/s12572-021-00304-x

• A Boltzmann scheme with physically relevant discrete velocities for Euler
equations

Abstract: Abstract Kinetic or Boltzmann schemes are interesting alternatives to the macroscopic numerical methods for solving the hyperbolic conservation laws of gas dynamics. They utilize the particle-based description instead of the wave propagation models. While the continuous particle velocity based upwind schemes were developed in the earlier decades, the discrete velocity Boltzmann schemes introduced in the last decade are found to be simpler and are easier to handle. In this work, we introduce a novel way of introducing discrete velocities which correspond to the physical wave speeds and formulate a discrete velocity Boltzmann scheme for solving Euler equations.
PubDate: 2021-09-01
DOI: 10.1007/s12572-021-00311-y

• New estimation method for periodic autoregressive time series of order 1

Abstract: Abstract The periodic behavior of real data can be manifested in the time series or in its characteristics. One of the characteristics that often manifests the periodic behavior is the sample autocovariance function. In this case, the periodically correlated (PC) behavior is considered. One of the main models that exhibits PC property is the periodic autoregressive (PARMA) model that is considered as the generalization of the classical autoregressive moving average (ARMA) process. However, when one considers the real data, practically the observed trajectory corresponds to the “pure” model with the additional noise which is a result of the noise of the measurement device or other external forces. Thus, in this paper we consider the model that is a sum of the periodic autoregressive (PAR) time series and the additive noise with finite-variance distribution. We present the main properties of the considered model indicating its PC property. One of the main goals of this paper is to introduce the new estimation method for the considered model’s parameters. The novel algorithm takes under consideration the additive noise in the model and can be considered as the modification of the classical Yule–Walker algorithm that utilizes the autocovariance function. Here, we propose two versions of the new method, namely the classical and the robust ones. The effectiveness of the proposed methodology is verified by Monte Carlo simulations. The comparison with the classical Yule–Walker method is presented. The approach proposed in this paper is universal and can be applied to any finite-variance models with the additive noise.
PubDate: 2021-09-01
DOI: 10.1007/s12572-021-00302-z

• Estimation of the parameters of vector autoregressive moving average
(VARMA) time series model with symmetric stable noise

Abstract: Abstract In this article, we propose the fractional lower-order covariance method (FLOC) for estimating the parameters of vector autoregressive moving average process (VARMA) of order p, q such that $$p, q\ge 1$$ with symmetric stable noise. Further, we show the efficiency, accuracy and simplicity of our methods through Monte Carlo simulation.
PubDate: 2021-09-01
DOI: 10.1007/s12572-021-00307-8

• Application of non-Gaussian multidimensional autoregressive model for
climate data prediction

Abstract: Abstract From the point of view of agriculture, ecology, or environmental engineering, the capability of forecasting meteorological variables in the long and short term is crucial. Short-term forecasts enabling the planning of field work in agriculture, management of mass events, or tourism are important, while long-term forecasts related to advancing climate change are also very interesting. In the literature, there are known many approaches that can be used to forecast climate time series. The most common is based on the statistical modelling of the corresponding data, and the prediction is made on the fitted model. There are known one-dimensional approaches, where single variables are modeled separately; however, in the last decade, there appears a new trend which assumes the importance of the relationship between different time series. This is the approach considered in this paper. We propose to examine the climate data (temperature and precipitation) using the multidimensional vector autoregressive model (VAR). However, because in the time series we observe non-Gaussian behaviour, the classical VAR model can not be applied and the multidimensional Gaussian noise is replaced by the $$\alpha -$$ stable one. This model was previously analyzed by the authors in the context of financial data description where also non-Gaussian characteristics are observed. The main goal of this paper is to answer the question whether there are reasons to go from the Gaussian model to the generalized models, like $$\alpha -$$ stable based. The second purpose is to link total precipitation data with temperature time series. In the classical approach, precipitation was treated as a variable not correlated with temperature, which, as we will show in the paper, is inconsistent with reality. We hope the presented in this paper results open new areas of interest related to climate data modelling and prediction.
PubDate: 2021-09-01
DOI: 10.1007/s12572-021-00300-1

• Numerical investigation of post-tensioned concrete slab developed by
hybrid concrete, PU foams, PVC, and GFRP

Abstract: Abstract In this study, 3D finite element analyses are conducted to quantify the mechanical behavior of the post-tensioned concrete deck and improve its efficiency as well as structural performance. The detailed finite element (FE) models consisting of interactions between the constituents based on experimental results are presented and validated with three experimental specimens tested under one-point loading. The FE models are dedicated to improve the structural behavior of the deck by reducing inefficient concrete in the tensile zone with three different strategies. First, the hybrid concrete design with different composition is proposed using the lightweight concrete presented in current research. Also, glass fiber-reinforced polymer (GFRP) is employed to enhance the strength of proposed hybrid decks. Second, the polyurethane (PU) foams with different properties are placed in the tensile part of deck without any changes in the total depth of control FE model and then the strength of PU decks is enhanced by estimating the minimum required thickness of GFRP layer. Besides, the PU foam decks with the same volume of concrete as control FE model are simulated. Finally, a design with polyvinyl chloride permanent formwork is numerically evaluated and studied in details. Regarding the FE analysis results, the efficiency of proposed decks is confirmed in comparison with control specimens. Decreasing the weight of deck as proposed in this research leads to decrease in dead and earthquake load and consequently in size and cost of designing the different parts of structures.
PubDate: 2021-06-11
DOI: 10.1007/s12572-021-00295-9

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