Results 21 to 30 of about 2,734,080 (302)
Network design for local agriculture using robust optimization
Information Processing in Agriculture, 2021 For small farmers wishing to sell their products under the “local agriculture” marketing concept, connecting with consumers can be challenging. One approach to mitigating this disconnect between where production occurs and where consumers reside is ...
Ashish Kambli, Ronald G. McGarvey
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Robustness and risk-sensitive filtering
Proceedings of the 36th IEEE Conference on Decision and Control, 2002 This paper gives a precise meaning to the robustness of risk-sensitive filters for problems in which one is uncertain as to the exact value of the probability model. It is shown that risk-sensitive estimators (including filters) enjoy an error bound which is the sum of two terms, the first of which coincides with an upper bound on the error that one ...
René K. Boel +2 more
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The contributions of interlocking loops and extensive nonlinearity to the properties of circadian clock models [PDF]
, 2010 Sensitivity and robustness are essential properties of circadian clock systems, enabling them to respond to the environment but resist noisy variations. These properties should be recapitulated in computational models of the circadian clock.
Andrew J Millar +15 more
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المجلة الدولية للأداء الاقتصادي, 2021 A Non-Homogeneous process is a process with rate parameter (t) such that this rate is a function of time. Bayesians are interested in robustness with respect to changes in prior distributions/sampling models/loss functions.
Fatiha TALBI
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ROBUSTNESS ESTIMATION OF FREE MOTION DEVIATIONS OF APERIODIC SYSTEMS WITH SENSITIVITY THEORY METHODS [PDF]
Научно-технический вестник информационных технологий, механики и оптики, 2018 Subject of Research.The paper deals with robustness estimation of free motion deviations in aperiodic continuous systemsto parameter variations of the state matrix. Methods.
N. A. Vunder, N. A. Dudarenko
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Comparisons of Robustness and Sensitivity between Cancer and Normal Cells by Microarray Data
Cancer Informatics, 2008 Robustness is defined as the ability to uphold performance in face of perturbations and uncertainties, and sensitivity is a measure of the system deviations generated by perturbations to the system.
Bor-Sen Chen, Liang-Hui Chu
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A Robust Class of Context-Sensitive Languages [PDF]
22nd Annual IEEE Symposium on Logic in Computer Science (LICS 2007), 2007 We define a new class of languages defined by multi-stack automata that forms a robust subclass of context-sensitive languages, with decidable emptiness and closure under boolean operations. This class, called multi-stack visibly pushdown languages (MVPLs), is defined using multi-stack pushdown automata with two restrictions: (a) the pushdown automaton
LA TORRE, Salvatore +2 more
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Approximation of achievable robustness limit based on sensitivity inversion [PDF]
, 2023 Introduction: The sensitivity function, defined as the closed-loop transfer function from the exogenous input to the tracking error, is central to the multi-objective design and analysis of a feedback control system.
Cho, Namhoon, Lee, Hae-In
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Robust Sensitivity Analysis for Stochastic Systems [PDF]
Mathematics of Operations Research, 2016 We study a worst-case approach to measure the sensitivity to model misspecification in the performance analysis of stochastic systems. The situation of interest is when only minimal parametric information is available on the form of the true model.
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ExtremeBounds: Extreme Bounds Analysis in R
Journal of Statistical Software, 2016 This article introduces the R package ExtremeBounds to perform extreme bounds analysis (EBA), a sensitivity test that examines how robustly the dependent variable of a regression model is related to a variety of possible determinants.
Marek Hlavac
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