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鲁东大学运筹学课件 Lecture-Dynamic Programming。
华南理工大学数据结构与算法课件Chapter13 Dynamic Programming
华南理工大学 数据结构 算法 课件 Chapter13 Dynamic Programming
2019/4/11
华南理工大学数据结构与算法课件Chapter13 Dynamic Programming。
Determining the optimal selling time of cattle:A stochastic dynamic programming approach
decision analysis farm management simulation
2016/11/11
The world meat market demands competitiveness, and optimal livestock replacement decisions can help to achieve this goal. In the article, there is introduced a novel discrete stochastic dynamic progra...
Obtaining Analytic Derivatives for a Class of Discrete-Choice Dynamic Programming Models
Analytic Derivatives Discrete-Choice Dynamic Programming Models
2015/9/18
This paper shows how to recursively calculate analytic first and second derivatives of the likelihood function generated by a popular version of a discrete-choice, dynamic programming model, allowing ...
SEMIAUTOMATIC ROAD EXTRACTION BY DYNAMIC PROGRAMMING OPTIMISATION IN THE OBJECT SPACE:SINGLE IMAGE CASE
Dynamic Programming road model feature extraction road extraction aerial images
2015/8/31
This article proposes a novel road extraction methodology from digital images. The innovation is based on the dynamic programming (DP) algorithm to carry out the optimisation process in the object spa...
SEMIAUTOMATIC ROAD EXTRACTION BY DYNAMIC PROGRAMMING OPTIMISATION IN THE OBJECT SPACE:SINGLE IMAGE CASE
Dynamic Programming road model feature extraction road extraction aerial images
2015/8/28
This article proposes a novel road extraction methodology from digital images. The innovation is based on the dynamic programming (DP) algorithm to carry out the optimisation process in the object spa...
Word Reordering and a Dynamic Programming Beam Search Algorithm for Statistical Machine Translation
Word Reordering Beam Search Algorithm Statistical Machine Translation
2015/8/28
In this article, we describe an efficient beam search algorithm for statistical machine translation based on dynamic programming (DP). The search algorithm uses the translation model presented in Brow...
Shrinking-horizon dynamic programming
dynamic programming model predictive control revenue management
2015/8/7
We describe a heuristic control policy, for a general finite-horizon stochastic control problem, that can be used when the current process disturbance is not conditionally independent of previous dist...
Min-max approximate dynamic programming
Dynamic planning policy dynamic system the noise the approximation function
2015/8/7
In this paper we describe an approximate dynamic programming policy for a discrete-time dynamical system perturbed by noise. The approximate value function is the pointwise supremum of a family of low...
Approximate dynamic programming via iterated Bellman inequalities
Convex Optimization Dynamic Programming Stochastic Control
2015/8/7
In this paper we introduce new methods for finding functions that lower bound the value function of a stochastic control problem, using an iterated form of the Bellman inequality. Our method is based ...
Quadratic approximate dynamic programming for input-affine systems
approximate dynamic programming stochastic control convex optimization
2015/8/7
We consider the use of quadratic approximate value functions for stochastic control problems with input-affine dynamics and convex stage cost and constraints. Evaluating the approximate dynamic progra...
Envelope condition method versus endogenous grid method for solving dynamic programming problems
Hoover Institution, Stanford University, USA University of Alicante, Spain
2015/7/21
We introduce an envelope condition method (ECM) for solving dynamic programming problems. The ECM method is simple to implement, dominates conventional value function iteration and is comparable in ac...
Shrinking-Horizon Dynamic Programming
dynamic programming model predictive control revenue management
2015/7/9
We describe a heuristic control policy, for a general finite-horizon stochastic control problem, that can be used when the current process disturbance is not conditionally independent of previous dist...
In this paper we describe an approximate dynamic programming policy for a discrete-time dynamical system perturbed by noise. The approximate value function is the pointwise supremum of a family of low...
Approximate Dynamic Programming via Iterated Bellman Inequalities
Convex Optimization Dynamic Programming Stochastic Control
2015/7/9
In this paper we introduce new methods for finding functions that lower bound the value function of a stochastic control problem, using an iterated form of the Bellman inequality. Our method is based ...