Results 1 to 10 of about 17,591 (152)
Probablistic convergence spaces and regularity [PDF]
International Journal of Mathematics and Mathematical Sciences, 1997 The usual definition of regularity for convergence spaces can be characterized by a diagonal axiom R due to Cook and Fischer. The generalization of R to the realm of probabilistic convergence spaces depends on a t-norm T, and the resulting axiom RT ...
P. Brock, D. C. Kent
doaj +3 more sources
Probabilistic convergence spaces and generalized metric spaces [PDF]
International Journal of Mathematics and Mathematical Sciences, 1998 The category PPRS(Δ), whose objects are probabilistic pretopological spaces which satisfy an axiom (Δ) and whose morphisms are continuous mappings, is introduced.
Paul Brock
doaj +3 more sources
I-convergence in probabilistic n-normed space
Soft Computing, 2012 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Binod Chandra Tripathy +2 more
exaly +5 more sources
Strong Statistical Convergence in Probabilistic Metric Spaces
Stochastic Analysis and Applications, 2008 In this article, we introduce the concepts of strongly statistically convergent sequence and strong statistically Cauchy sequence in a probabilistic metric (PM) space endowed with the strong topology, and establish some basic facts. Next, we define the strong statistical limit points and the strong statistical cluster points of a sequence in this space
Serpil Pehlivan
exaly +5 more sources
Strong Γ-ideal convergence in a probabilistic normed space
Topology and Its Applications, 2016 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Serpil Pehlivan
exaly +4 more sources
Succession-diagram-based Markov chains reveal the attractor landscape of asynchronous Boolean networks [PDF]
npj Systems Biology and ApplicationsComprehensive analysis of the dynamics of Boolean models of biological systems is hampered by the exponentially large state space. Here we introduce the succession-diagram-based Markov chain (SD Markov chain), a coarse-grained representation that uses ...
Kyu Hyong Park, Réka Albert
doaj +2 more sources
Strong ideal convergence in probabilistic metric spaces
Proceedings of the Indian Academy of Sciences: Mathematical Sciences, 2009 The authors introduce the notion of strong ideal convergence in Probabilistic Metric (=PM) spaces. Let \({\mathcal I}\) be an ideal in \(\mathbb N\) (\(A\cup B\in{\mathcal I}\) if \(A,B\in{\mathcal I}\) and \(B\in{\mathcal I}\) if \(B\subset A\in{\mathcal I}\)).
Serpil Pehlivan
exaly +5 more sources
Topological Progress Potential-Enhanced Continuous-Space Ant Colony Algorithm for Robot Path Planning [PDF]
SensorsTo address the issues of traditional grid-based Ant Colony Optimization path planning in discretized continuous space—including limited direction freedom, lack of global topological guidance, and difficulty in balancing path smoothness and safety margin ...
Guikun Dong +5 more
doaj +2 more sources
Minimization of weight in truss structures under probabilistic constrains [PDF]
مجله مدل سازی در مهندسی, 2021 The main purpose of the reliability theory of structural systems is the optimal design based on the reliability concept. Trusses and space structures are widely used, and cost and safety both are important in these structures.
Mohammad Reza Mostakhdemin Hosseini
doaj +1 more source
Probabilistic modular metric spaces [PDF]
Journal of Hyperstructures, 2020 The purpose of this study is to investigate the connection between probabilistic and modular metric spaces. We discussseveral important properties such as convergence and completeness,etc, and the relationship among the mentioned properties in the ...
Kianoush Fathi Vajargah +1 more
doaj +1 more source