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96 612 (0,14s)

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Decomposition in multistage stochastic programs with individual probability constrains

(mostly conditional) expectation in the individual objective functions. The constraints set can (generally) depend on the "underlying" probability measure. In the paper, the case of individual probability cons...

BB - Aplikovaná statistika, operační výzkum

  • 2006
  • D
Result

Comparison of methods for constrained design of computer experiments

, development of meta-models, sensitivity analysis or probability calculations. The creation of dependent input variables the design domain is constrained. Therefore classical designs comparison of several methods for designs in

JM - Inženýrské stavitelství

  • 2014
  • D
Result

Languages for Constrained Binary Segmentation Based on Maximum A Posteriori Probability Labeling

MRF with asymmetric pairwise compatibility constraints between direct pixel neighbors solves a constrained binary image segmentation task. The model is constraining shape and alignment of individual contiguous binary segmen...

JD - Využití počítačů, robotika a její aplikace

  • 2009
  • Jx
Result

Evolution of clonal growth forms in angiosperms

or the constraining role they play on clonal traits. We investigated the rates of evolutionary change by which individual CGOs are acquired and lost using a set of 2652 species of Central European flora. Furthermore, we asked how t...

Plant sciences, botany

  • 2020
  • Jimp
  • Link
Result

Reinforcement Learning of Risk-Constrained Policies in Markov Decision Processes

probability catastrophic events with highly negative impact on the system. On the other hand, risk-averse policies require the probability of undesirable events represent catastrophic outcomes. The objective of risk-constrained...

Computer and information sciences

  • 2020
  • D
  • Link
Result

Weak Structural Dependence in Chance-Constrained Programming

In chance -constrained optimization problems, a solution is assumed to be feasible only with certain, sufficiently high probability. For computational and theoretical purposes, the convexity property of the resulting constraint set ...

IN - Informatika

  • 2008
  • D
Result

Bayesian State Estimation Using Constrained Zonotopes

This paper proposes an approximate Bayesian recursive algorithm for the state estimation of a linear discrete-time stochastic state-space model. The involved state and observation noises are assumed to be bounded and uniformly distributed. The suppor...

Automation and control systems

  • 2023
  • D
  • Link
Result

Design of Confidence Sets for Estimation with Approximate Piecewise Linear Constraint

Constrained state estimation has been studied in the literature usually from the point estimation perspective. That is, a random vector is designed and its the unknown state with a predefined probability is constructed for a Gaussia...

Automation and control systems

  • 2020
  • D
  • Link
Result

A Note on Optimization under Uncertainty: Comparing Probabilistically Constrained and Robust Optimization Methodology

. In this paper, we concentrate on two specific approaches, namely on chance constrained (stochastic) and robust optimization. Chance (probabilistically) constrained optimization is based on the assumption that underlying uncertaint...

BB - Aplikovaná statistika, operační výzkum

  • 2016
  • D
Result

An AF performance analysis in the energy harvesting relaying network

, the energy constrained relays harvest energy from the received signal and then use is also investigated at the same time. Finally, we consider the outage probability......

Telecommunications

  • 2017
  • D
  • Link
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