International Journal of Applied Mathematics and Computer Science (INT J AP MAT COM-POL )

Publisher: Uniwersytet Zielonogórski; Lubuskie Towarzystwo Naukowe

Description

The International Journal of Applied Mathematics and Computer Science is a quarterly published jointly by the University of Zielona óra and the Lubuskie Scientific Society in Zielona óra, Poland, since 1991. The Journal strives to meet the demand for the presentation of interdisciplinary research concerned with applications of mathematical methods to computer science and engineering. It publishes high quality original research results in the following areas: mathematical methods in computer science and engineering; modern control theory and applications; artificial intelligence techniques; applied mathematics and mathematical optimization techniques.

  • Impact factor
    1.01
    Show impact factor history
     
    Impact factor
  • 5-year impact
    1.15
  • Cited half-life
    5.10
  • Immediacy index
    0.17
  • Eigenfactor
    0.00
  • Article influence
    0.26
  • Website
    International Journal of Applied Mathematics and Computer Science (AMCS) website
  • Other titles
    International journal of applied mathematics and computer science (Online)
  • ISSN
    1641-876X
  • OCLC
    54678624
  • Material type
    Document, Periodical, Internet resource
  • Document type
    Internet Resource, Computer File, Journal / Magazine / Newspaper

Publications in this journal

  • [Show abstract] [Hide abstract]
    ABSTRACT: Systems based on principal component analysis have developed from exploratory data analysis in the past to current data processing applications which encode and decode vectors of data using a changing projection space (eigenspace). Linear systems, which need to be solved to obtain a constantly updated eigenspace, have increased significantly in their dimensions during this evolution. The basic scheme used for updating the eigenspace, however, has remained basically the same: (re)computing the eigenspace whenever the error exceeds a predefined threshold. In this paper we propose a computationally efficient eigenspace updating scheme, which specifically supports high-dimensional systems from any domain. The key principle is a prior selection of the vectors used to update the eigenspace in combination with an optimized eigenspace computation. The presented theoretical analysis proves the superior reconstruction capability of the introduced scheme, and further provides an estimate of the achievable compression ratios.
    International Journal of Applied Mathematics and Computer Science 01/2014; 24(1):123-141.
  • [Show abstract] [Hide abstract]
    ABSTRACT: The feature selection problem often occurs in pattern recognition and, more specifically, classification. Although these patterns could contain a large number of features, some of them could prove to be irrelevant, redundant or even detrimental to classification accuracy. Thus, it is important to remove these kinds of features, which in turn leads to problem dimensionality reduction and could eventually improve the classification accuracy. In this paper an approach to dimensionality reduction based on differential evolution which represents a wrapper and explores the solution space is presented. The solutions, subsets of the whole feature set, are evaluated using the k-nearest neighbour algorithm. High quality solutions found during execution of the differential evolution fill the archive. A final solution is obtained by conducting k-fold cross-validation on the archive solutions and selecting the best one. Experimental analysis is conducted on several standard test sets. The classification accuracy of the k-nearest neighbour algorithm using the full feature set and the accuracy of the same algorithm using only the subset provided by the proposed approach and some other optimization algorithms which were used as wrappers are compared. The analysis shows that the proposed approach successfully determines good feature subsets which may increase the classification accuracy.
    International Journal of Applied Mathematics and Computer Science 01/2014; 24(1):111-122.
  • [Show abstract] [Hide abstract]
    ABSTRACT: The work concerns formal verification of workflow-oriented software models using deductive approach. The formal correctness of a model's behaviour is considered. Manually building logical specifications, which are considered as a set of temporal logic formulas, seems to be the significant obstacle for an inexperienced user when applying the deductive approach. A system, and its architecture, for the deduction-based verification of workflow-oriented models is proposed. The process of inference is based on the semantic tableaux method which has some advantages when compared to traditional deduction strategies. The algorithm for an automatic generation of logical specifications is proposed. The generation procedure is based on the predefined workflow patterns for BPMN, which is a standard and dominant notation for the modeling of business processes. The main idea for the approach is to consider patterns, defined in terms of temporal logic, as a kind of (logical) primitives which enable the transformation of models to temporal logic formulas constituting a logical specification. Automation of the generation process is crucial for bridging the gap between intuitiveness of the deductive reasoning and the difficulty of its practical application in the case when logical specifications are built manually. This approach has gone some way towards supporting, hopefully enhancing our understanding of, the deduction-based formal verification of workflow-oriented models.
    International Journal of Applied Mathematics and Computer Science 01/2014;
  • [Show abstract] [Hide abstract]
    ABSTRACT: Traditional traffic control systems based on traffic light have achieved a great success in reducing the average delay of vehicles or in improving the traffic capacity. The main idea of these systems is based on the optimization of the cycle time, the phase sequence, and the phase duration. The right-of-ways are assigned to vehicles of one or several movements for a specific time. With the emergence of cooperative driving, an innovative traffic control concept, Autonomous Intersection Management (AIM), has emerged. In the framework of AIM, the right-of-way is customized on the measurement of the vehicle state and the traffic control turns to determine the passing sequence of vehicles. Since each vehicle is considered individually, AIM faces a combinatorial optimization problem. This paper proposes a dynamic programming algorithm to find its optimal solution in polynomial time. Experimental results obtained by simulation show that the proper arrangement of the vehicle passing sequence can greatly improve traffic efficiency at intersections.
    International Journal of Applied Mathematics and Computer Science 12/2013; 23(4):773-785.
  • [Show abstract] [Hide abstract]
    ABSTRACT: In order to design an interconnection network, it is essential to have a comprehensive understanding about properties and limitations of the network. These properties and limitations are characterized by the topology of the network. Since a topology sets constraints and costs, it plays a critical role in all interconnection networks. Different topologies have been proposed for interconnection networks in literature. The Generalized Hypercube is one of the oldest topologies that can be mentioned. Recently a group of researchers at HP Lab have introduced a new topology for these networks, called HyperX. Despite of many similarities between these two topologies, there are significant differences between their performances and costs. It seems that this important issue has been neglected in contexts of interconnection networks. In this paper, we compare HyperX and Generalized Hypercube topologies under some key topological measures. We show that HyperX is somehow better than Generalized Hypercube in the sense of topological properties.
    International Journal of Applied Mathematics and Computer Science 10/2013; 9(2):111-122.
  • [Show abstract] [Hide abstract]
    ABSTRACT: In this paper the problem of European option valuation in a Levy process setting is analysed. In our model the underlying asset follows a geometric Levy process. The jump part of the log-price process, which is a linear combination of Poisson processes, describes upward and downward jumps in price. The proposed pricing method is based on stochastic analysis and the theory of fuzzy sets.We assume that some parameters of the financial instrument cannot be precisely described and therefore they are introduced to the model as fuzzy numbers. Application of fuzzy arithmetic enables us to consider various sources of uncertainty, not only the stochastic one. To obtain the European call option pricing formula we use the minimal entropy martingale measure and Levy characteristics.
    International Journal of Applied Mathematics and Computer Science 09/2013; 23(3):613-622.

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