Results 81 to 90 of about 399,699 (283)
Вестник Донского государственного технического университета, 2018 The issues concerning the potential application of Markov processes theory for efficient management decision making based on the production enterprise business modeling are considered.
Evgeniya R. Khabibullina
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The Geography of Success: A Spatial Analysis of Export Intensity in the Italian Wine Industry
Agribusiness, EarlyView.ABSTRACT This paper investigates the paradox of how Italy's fragmented, SME‐dominated wine industry achieves global export success. Moving beyond purely firm‐centric explanations, we test whether export intensity is spatially dependent, clustering geographically in regional ecosystems.
Nicolas Depetris Chauvin, Jonas Di Vita
wiley +1 more source
A Novel Robust Interacting Multiple Model Algorithm for Maneuvering Target Tracking
Advances in Electrical and Computer Engineering, 2017 In this paper, the state estimation problem for discrete-time jump Markov systems is considered. A minimax filtering technique, interacting multiple model algorithm based on game theory, is developed for discrete-time stochastic systems.
GHAZAL, M., DOUSTMOHAMMADI, A.
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Journal of Agricultural and Resource Economics, 2002 This study investigates the costs of subsidies for land retention and conversion, in addition to a policy that combines the incentives. A Markov model of forest and agricultural land use is estimated for the U.S. South Central region and used to simulate
Andrew J. Plantinga, Soeun Ahn
doaj +1 more source
Convergences and projection Markov property of Markov processes on ultrametric spaces
, 2014 Let $(S,\rho)$ be an ultrametric space with certain conditions and $S^k$ be the quotient space of $S$ with respect to the partition by balls with a fixed radius $\phi(k)$.
Suzuki, Kohei
core +1 more source
AIChE Journal, EarlyView.Abstract Bayesian estimation enables uncertainty quantification, but analytical implementation is often intractable. As an approximate approach, the Markov Chain Monte Carlo (MCMC) method is widely used, though it entails a high computational cost due to frequent evaluations of the likelihood function.
Tatsuki Maruchi +2 more
wiley +1 more source
Unsupervised SAR image segmentation based on kernel TMFs with belief propagation
The Journal of Engineering, 2019 The triplet Markov field (TMF) model has achieved promising results in synthetic aperture radar (SAR) image segmentation. Focusing on the simple likelihood modelling of an SAR image and the effective optimisation of the TMF model, an unsupervised SAR ...
Lu Gan, Xiaoming Liu, Ziwei Li
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Approximation of symmetrizations by Markov processes
, 2016 Under continuity and recurrence assumptions, we prove that the iteration of successive partial symmetrizations that form a time-homogeneous Markov process, converges to a symmetrization.
Dekeyser, Justin, Van Schaftingen, Jean
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Graph‐based imitation and reinforcement learning for efficient Benders decomposition
AIChE Journal, EarlyView.Abstract This work introduces an end‐to‐end graph‐based agent for accelerating the computational efficiency of Benders Decomposition. The agent's policy is parameterized by a graph neural network, which takes as input a bipartite graph representation of the master problem and proposes a candidate solution.
Bernard T. Agyeman +3 more
wiley +1 more source
Scanning of Markov Random Processes
Advances in Electrical and Electronic Engineering, 2003 Function of most electronic devices is based on the microprocessor control. A microprocessor must scan and evaluate function of many controlled equipment that can be transformed into 2 statuses - "free" or "busy".
Gustav Cepciansky
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