stochastic dynamic
Stochastic Dynamic Optimization in Spatial and Network Resource Economic Models.
... imate dynamic programming (ADP) methods (Powell 2011) in obtaining good policy rules for stochastic dynamic spatial problems where dynamic programming is deemed ...species stochastic ...
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OPTIMAL RESERVOIR OPERATING POLICIES ? A STOCHASTIC DYNAMIC PROGRAMMING APPROACH
... DISCUSSION: Stochastic dynamic programming model described above is applied to single reservoir for determining optimal monthly operating rules under three ...
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Persistently optimal policies in stochastic dynamic programming with generalized discounting
... the stochastic decision process and then use their expected values (the von Neumann-Morgenstern ...of stochastic growth models, and therefore embraces also those studied by Brock and Mirman (1972), Stokey ...
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Stochastic dynamic Thurstone Mosteller models for sports tournaments
... In this paper, we analyse the results of double round-robin tournaments from the last per- spective, that is modelling the outcomes of matches. Since we are interested in studying how the strengths of the teams evolve ...
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Optimal Amount and Timing of Investment in a Stochastic Dynamic Cournot Competition
... Structure of this paper is as follows. Section 2 lays out a stochastic dynamic Cournot model and derives the conditions for the optimal amounts of the output and the investment. Section 3 derives the ...
6
Modelling and Decision-making on Deteriorating Production Systems using Stochastic Dynamic Programming Approach
... 10. Fallahnezhad M.S., Niaki S.T.A. "A multi-stage two-machines replacement strategy using mixture models, Bayesian inference and stochastic dynamic programming",Communications in Statistics-Theory ...
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Stochastic dynamic programming methods for the portfolio selection problem
... Note that the linear approximation methods are quite naive but due to their sim- plicity they have been extensively used and have many applications in various fields (see for example [61] for an application in wireless ...
253
Adaptation in Stochastic Dynamic Systems—Survey and New Results I
... is a realization of a stochastic process on a probability space where the measure on the space is such that a form of ergodicity holds. For the purposes of this paper, it is sufficient to require the ergodicity in ...
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Adaptation in Stochastic Dynamic Systems—Survey and New Results II
... It would be fortunate if someone managed to measure adequacy of a model in state space, considering that, as defined by Kalman [9], state space is a set of inner states of a system, which is rich enough to house all ...
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Performance Analysis of Dynamic and Static Facility Layouts in a Stochastic Environment
... the stochastic dynamic (or multi-period) problem, two new quadratic assignment-based mathematical models corresponding to the dynamic and static approaches are ...The dynamic programming ...
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Dynamic asset allocation for bank under stochastic interest rates
... using stochastic con- trol theory, developed by Merton [13, 14] in discrete and continuous-time setting (See, for instance, Sørensen, [21], Kim and Omberg, [11], Wachter, [22], Campbell and Vieceira, [3], and ...
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Irrigation Operating Policies Using Genetic Algorithm Ukai Reservoir as a Case Study
... deriving the optimal operating policy and compared its performance with that of stochastic dynamic programming (SDP) for a multipurpose reservoir. The objective function of both GA and SDP was to minimize ...
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Non Stationary Stochastic Volatility Model for Dynamic Feedback and Skewness
... The affine combination of positive factor with symmetric innovation results in a skewed family of distributions. The impact parameters determine the amount and direction of conditional skewness in the corresponding ...
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Adaptive observer based non linear stochastic system control with sliding mode schemes
... nonlinear stochastic systems with uncertainties from the measurable system output and the reconstructed states are employed to construct a sliding mode controller for the stabilization control of complex nonlinear ...
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A. Stochastic Scheduling
... Stochastic Scheduling Stochastic project scheduling views scheduling as a multi-stage decision process which requires making dynamic scheduling decisions at stochastic decision points co[r] ...
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Dynamic programming for parsing and estimation of stochastic unification based grammars
... require stochastic models more general than Probabilis- tic Context-Free Grammars (PCFGs) and Markov Branching Processes, and proposed the use of log- linear models for defining probability distributions over the ...
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Simple techniques for likelihood analysis of univariate and multivariate stable distributions: with extensions to multivariate stochastic volatility and dynamic factor models
... Simple techniques for likelihood analysis of univariate and multivariate stable distributions: with extensions to multivariate stochastic volatility and dynamic factor models Tsionas, Mi[r] ...
61
Optimal Income Taxation with a Stationarity Constraint in a Dynamic Stochastic Economy
... our dynamic stochastic economy, the support of types will move over time, and a direct application of the static arguments implies that the marginal tax rate is zero at the top of the expanded type space, ...
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Learning Latent Trees with Stochastic Perturbations and Differentiable Dynamic Programming
... We build a simple network where a BiLSTM is followed by deep dotted attention which computes the dependency weights (see Equation 1). In these experiments, unlike Section 6, GCN does not have access to input tokens (or ...
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Optimal income taxation with a stationarity constraint in a dynamic stochastic economy
... We consider the optimal nonlinear income taxation problem in a dynamic, stochastic environment when the government cannot change the tax rule as uncertainty resolves. Due to such a stationarity constraint, ...
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