Subjects -> MATHEMATICS (Total: 1013 journals)
    - APPLIED MATHEMATICS (92 journals)
    - GEOMETRY AND TOPOLOGY (23 journals)
    - MATHEMATICS (714 journals)
    - MATHEMATICS (GENERAL) (45 journals)
    - NUMERICAL ANALYSIS (26 journals)
    - PROBABILITIES AND MATH STATISTICS (113 journals)

MATHEMATICS (714 journals)            First | 1 2 3 4 | Last

Showing 201 - 400 of 538 Journals sorted alphabetically
Educação Matemática Debate     Open Access  
Edumatica : Jurnal Pendidikan Matematika     Open Access  
EduMatSains     Open Access  
Electronic Journal of Differential Equations     Open Access  
Electronic Journal of Graph Theory and Applications     Open Access   (Followers: 3)
Em Teia : Revista de Educação Matemática e Tecnológica Iberoamericana     Open Access  
Emergent Scientist     Open Access  
Energy for Sustainable Development     Hybrid Journal   (Followers: 13)
Enseñanza de las Ciencias : Revista de Investigación y Experiencias Didácticas     Open Access  
Entropy     Open Access   (Followers: 5)
ESAIM: Control Optimisation and Calculus of Variations     Open Access   (Followers: 2)
Euclid     Open Access  
European Journal of Applied Mathematics     Hybrid Journal  
European Journal of Combinatorics     Full-text available via subscription   (Followers: 3)
European Journal of Mathematics     Hybrid Journal   (Followers: 1)
European Scientific Journal     Open Access   (Followers: 1)
Examples and Counterexamples     Open Access  
Experimental Mathematics     Hybrid Journal   (Followers: 5)
Expositiones Mathematicae     Hybrid Journal   (Followers: 2)
Extracta Mathematicae     Open Access  
Facta Universitatis, Series : Mathematics and Informatics     Open Access  
Finite Fields and Their Applications     Full-text available via subscription   (Followers: 5)
Fixed Point Theory and Applications     Open Access  
Formalized Mathematics     Open Access  
Forum of Mathematics, Pi     Open Access   (Followers: 1)
Forum of Mathematics, Sigma     Open Access   (Followers: 1)
Foundations and Trends® in Econometrics     Full-text available via subscription   (Followers: 6)
Foundations and Trends® in Networking     Full-text available via subscription   (Followers: 1)
Foundations and Trends® in Stochastic Systems     Full-text available via subscription   (Followers: 1)
Foundations and Trends® in Theoretical Computer Science     Full-text available via subscription   (Followers: 1)
Foundations of Computational Mathematics     Hybrid Journal  
Fractal and Fractional     Open Access  
Fractals     Hybrid Journal   (Followers: 1)
Frontiers of Mathematics in China     Hybrid Journal  
Fuel Cells Bulletin     Full-text available via subscription   (Followers: 9)
Functional Analysis and Other Mathematics     Hybrid Journal   (Followers: 4)
Fundamental Journal of Mathematics and Applications     Open Access  
Funktsional'nyi Analiz i ego Prilozheniya     Full-text available via subscription  
Fuzzy Optimization and Decision Making     Hybrid Journal   (Followers: 8)
Game Theory     Open Access   (Followers: 2)
Games     Open Access   (Followers: 4)
Games and Economic Behavior     Hybrid Journal   (Followers: 25)
Gamm - Mitteilungen     Hybrid Journal  
GANIT : Journal of Bangladesh Mathematical Society     Open Access  
GEM - International Journal on Geomathematics     Hybrid Journal   (Followers: 1)
General Mathematics     Open Access  
Glasgow Mathematical Journal     Full-text available via subscription  
Global Journal of Mathematical Sciences     Full-text available via subscription  
Graphs and Combinatorics     Hybrid Journal   (Followers: 4)
Grey Systems : Theory and Application     Hybrid Journal  
Groups, Complexity, Cryptology     Open Access   (Followers: 2)
GSTF Journal of Mathematics, Statistics and Operations Research     Open Access   (Followers: 1)
Historia Mathematica     Full-text available via subscription  
Historical Methods: A Journal of Quantitative and Interdisciplinary History     Hybrid Journal   (Followers: 28)
IMA Journal of Applied Mathematics     Hybrid Journal  
IMA Journal of Numerical Analysis - advance access     Hybrid Journal  
ImmunoInformatics     Open Access   (Followers: 1)
Indagationes Mathematicae     Open Access  
Indian Journal of Pure and Applied Mathematics     Hybrid Journal   (Followers: 4)
Indonesian Journal of Combinatorics     Open Access  
Indonesian Journal of Science and Mathematics Education     Open Access   (Followers: 1)
Infinite Dimensional Analysis, Quantum Probability and Related Topics     Hybrid Journal   (Followers: 1)
Infinity Jurnal Matematika dan Aplikasinya     Open Access   (Followers: 3)
Information and Inference     Free  
InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan     Open Access  
InfraMatics     Open Access  
Insight - Non-Destructive Testing and Condition Monitoring     Full-text available via subscription   (Followers: 110)
International Electronic Journal of Algebra     Open Access  
International Journal for Numerical Methods in Engineering     Hybrid Journal   (Followers: 35)
International Journal for Numerical Methods in Fluids     Hybrid Journal   (Followers: 19)
International Journal of Advanced Mathematical Sciences     Open Access  
International Journal of Advanced Mechatronic Systems     Hybrid Journal   (Followers: 2)
International Journal of Advanced Research in Mathematics     Open Access  
International Journal of Advances in Engineering Sciences and Applied Mathematics     Hybrid Journal   (Followers: 10)
International Journal of Algebra and Computation     Hybrid Journal   (Followers: 1)
International Journal of Algebra and Statistics     Open Access   (Followers: 3)
International Journal of Applied and Computational Mathematics     Hybrid Journal  
International Journal of Applied Mathematical Research     Open Access   (Followers: 1)
International Journal of Applied Mathematics and Computer Science     Open Access   (Followers: 7)
International Journal of Applied Mechanics     Hybrid Journal   (Followers: 8)
International Journal of Applied Nonlinear Science     Hybrid Journal  
International Journal of Autonomic Computing     Hybrid Journal   (Followers: 1)
International Journal of Bifurcation and Chaos     Hybrid Journal   (Followers: 4)
International Journal of Biomathematics     Hybrid Journal   (Followers: 2)
International Journal of Computational Complexity and Intelligent Algorithms     Hybrid Journal  
International Journal of Computational Economics and Econometrics     Hybrid Journal   (Followers: 6)
International Journal of Computational Geometry and Applications     Hybrid Journal   (Followers: 2)
International Journal of Computational Intelligence and Applications     Hybrid Journal   (Followers: 2)
International Journal of Computational Methods     Hybrid Journal   (Followers: 4)
International Journal of Computer Processing Of Languages     Hybrid Journal   (Followers: 1)
International Journal of Control, Automation and Systems     Hybrid Journal   (Followers: 15)
International Journal of Dynamical Systems and Differential Equations     Hybrid Journal   (Followers: 1)
International Journal of Economics and Accounting     Hybrid Journal   (Followers: 1)
International Journal of Foundations of Computer Science     Hybrid Journal   (Followers: 3)
International Journal of Fuzzy Computation and Modelling     Hybrid Journal   (Followers: 2)
International Journal of Image and Graphics     Hybrid Journal   (Followers: 5)
International Journal of Industrial Electronics and Drives     Hybrid Journal   (Followers: 3)
International Journal of Low-Carbon Technologies     Open Access   (Followers: 1)
International Journal of Mathematical Education in Science and Technology     Hybrid Journal   (Followers: 9)
International Journal of Mathematical Modelling & Computations     Open Access   (Followers: 3)
International Journal of Mathematical Modelling and Numerical Optimisation     Hybrid Journal   (Followers: 5)
International Journal of Mathematical Sciences and Computing     Open Access  
International Journal of Mathematics     Hybrid Journal   (Followers: 4)
International Journal of Mathematics & Computation     Full-text available via subscription  
International Journal of Mathematics and Mathematical Sciences     Open Access   (Followers: 4)
International Journal of Mathematics in Operational Research     Hybrid Journal   (Followers: 2)
International Journal of Metaheuristics     Hybrid Journal   (Followers: 1)
International Journal of Modelling in Operations Management     Hybrid Journal   (Followers: 2)
International Journal of Modern Nonlinear Theory and Application     Open Access   (Followers: 1)
International Journal of Number Theory     Hybrid Journal   (Followers: 1)
International Journal of Partial Differential Equations     Open Access   (Followers: 2)
International Journal of Polymer Science     Open Access   (Followers: 25)
International Journal of Pure Mathematical Sciences     Open Access  
International Journal of Reliability, Quality and Safety Engineering     Hybrid Journal   (Followers: 14)
International Journal of Research in Undergraduate Mathematics Education     Hybrid Journal   (Followers: 4)
International Journal of Sediment Research     Full-text available via subscription   (Followers: 2)
International Journal of Shape Modeling     Hybrid Journal   (Followers: 1)
International Journal of Theoretical and Mathematical Physics     Open Access   (Followers: 13)
International Journal of Trends in Mathematics Education Research     Open Access   (Followers: 4)
International Journal of Ultra Wideband Communications and Systems     Hybrid Journal  
International Journal of Wavelets, Multiresolution and Information Processing     Hybrid Journal  
International Journal on Artificial Intelligence Tools     Hybrid Journal   (Followers: 9)
International Mathematics Research Notices     Hybrid Journal   (Followers: 1)
Internet Mathematics     Hybrid Journal   (Followers: 1)
Inventiones mathematicae     Hybrid Journal   (Followers: 2)
Inverse Problems in Science and Engineering     Hybrid Journal   (Followers: 3)
Investigations in Mathematics Learning     Hybrid Journal  
Iranian Journal of Optimization     Open Access   (Followers: 2)
Israel Journal of Mathematics     Hybrid Journal  
Ithaca : Viaggio nella Scienza     Open Access  
ITM Web of Conferences     Open Access  
Izvestiya Rossiiskoi Akademii Nauk. Seriya Matematicheskaya     Full-text available via subscription  
Jahresbericht der Deutschen Mathematiker-Vereinigung     Hybrid Journal  
Japan Journal of Industrial and Applied Mathematics     Hybrid Journal  
Japanese Journal of Mathematics     Hybrid Journal  
JIPM (Jurnal Ilmiah Pendidikan Matematika)     Open Access  
JMPM : Jurnal Matematika dan Pendidikan Matematika     Open Access  
JOHME : Journal of Holistic Mathematics Education     Open Access   (Followers: 3)
Johnson Matthey Technology Review     Open Access  
Jornal Internacional de Estudos em Educação Matemática     Open Access  
Journal d'Analyse Mathématique     Hybrid Journal   (Followers: 2)
Journal de Mathématiques Pures et Appliquées     Full-text available via subscription   (Followers: 3)
Journal for Research in Mathematics Education     Full-text available via subscription   (Followers: 29)
Journal für Mathematik-Didaktik     Hybrid Journal  
Journal of Advanced Mathematics and Applications     Full-text available via subscription   (Followers: 1)
Journal of Algebra     Full-text available via subscription   (Followers: 3)
Journal of Algebra and Its Applications     Hybrid Journal   (Followers: 3)
Journal of Algebraic Combinatorics     Hybrid Journal   (Followers: 3)
Journal of Algorithms & Computational Technology     Open Access  
Journal of Applied Mathematics     Open Access   (Followers: 3)
Journal of Applied Mathematics and Computing     Hybrid Journal  
Journal of Applied Mathematics, Statistics and Informatics     Open Access   (Followers: 1)
Journal of Artificial Intelligence and Data Mining     Open Access   (Followers: 10)
Journal of Classification     Hybrid Journal   (Followers: 5)
Journal of Combinatorial Designs     Hybrid Journal   (Followers: 4)
Journal of Combinatorial Optimization     Hybrid Journal   (Followers: 7)
Journal of Combinatorial Theory, Series A     Full-text available via subscription   (Followers: 5)
Journal of Combinatorial Theory, Series B     Full-text available via subscription   (Followers: 3)
Journal of Complex Analysis     Open Access   (Followers: 2)
Journal of Complex Networks     Hybrid Journal   (Followers: 1)
Journal of Complexity     Hybrid Journal   (Followers: 6)
Journal of Computational and Applied Mathematics     Hybrid Journal   (Followers: 6)
Journal of Computational Biology     Hybrid Journal   (Followers: 9)
Journal of Computational Mathematics and Data Science     Open Access  
Journal of Computational Multiphase Flows     Open Access   (Followers: 1)
Journal of Computational Physics     Hybrid Journal   (Followers: 59)
Journal of Computational Physics : X     Open Access   (Followers: 1)
Journal of Computer Engineering, System and Science (CESS)     Open Access  
Journal of Contemporary Mathematical Analysis     Hybrid Journal  
Journal of Cryptology     Hybrid Journal   (Followers: 5)
Journal of Difference Equations and Applications     Hybrid Journal  
Journal of Differential Equations     Full-text available via subscription   (Followers: 1)
Journal of Discrete Mathematics     Open Access   (Followers: 1)
Journal of Dynamics and Differential Equations     Hybrid Journal  
Journal of Engineering Mathematics     Hybrid Journal   (Followers: 2)
Journal of Evolution Equations     Hybrid Journal  
Journal of Experimental Algorithmics     Full-text available via subscription  
Journal of Flood Risk Management     Hybrid Journal   (Followers: 14)
Journal of Function Spaces     Open Access  
Journal of Functional Analysis     Full-text available via subscription   (Followers: 3)
Journal of Geochemical Exploration     Hybrid Journal   (Followers: 4)
Journal of Geological Research     Open Access   (Followers: 1)
Journal of Geovisualization and Spatial Analysis     Hybrid Journal  
Journal of Global Optimization     Hybrid Journal   (Followers: 6)
Journal of Global Research in Mathematical Archives     Open Access  
Journal of Homotopy and Related Structures     Hybrid Journal  
Journal of Honai Math     Open Access  
Journal of Humanistic Mathematics     Open Access   (Followers: 1)
Journal of Hyperbolic Differential Equations     Hybrid Journal  
Journal of Indian Council of Philosophical Research     Hybrid Journal  
Journal of Industrial Mathematics     Open Access   (Followers: 2)
Journal of Inequalities and Applications     Open Access  
Journal of Infrared, Millimeter and Terahertz Waves     Hybrid Journal   (Followers: 3)
Journal of Integrable Systems     Open Access  
Journal of Knot Theory and Its Ramifications     Hybrid Journal   (Followers: 2)
Journal of Liquid Chromatography & Related Technologies     Hybrid Journal   (Followers: 7)
Journal of Logical and Algebraic Methods in Programming     Hybrid Journal   (Followers: 1)
Journal of Manufacturing Systems     Full-text available via subscription   (Followers: 3)
Journal of Mathematical Analysis and Applications     Full-text available via subscription   (Followers: 3)
Journal of mathematical and computational science     Open Access   (Followers: 2)

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

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      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

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      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

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      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

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      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

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      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

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      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

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      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

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      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

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      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

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      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

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      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

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      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

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      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

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      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

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      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

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      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
           with additive noise

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      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

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      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

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      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

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      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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