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平均代价
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  average cost
     OPTIMALITY STRATEGY OF AVERAGE COST BASED PERFORMANCE POTENTIALS FOR MARKOV CONTROL PROCESS
     Markov控制过程基于性能势的平均代价最优策略
短句来源
     Under quite general assumptions, the optimality equation is directly established and the existence theorem of optimal solution is proved for infinite time average cost model in a compact action set by using basic properties of the Markov performance potentials.
     应用Markov性能势的基本性质 ,在很一般性的假设条件下 ,直接导出了无限时间平均代价模型在紧致行动集上的最优性方程及其解的存在性定理 .
短句来源
     This paper deals with the average cost optimization problem for a class of discrete time Markov control processes.
     研究了一类离散时间 Markov控制过程平均代价性能最优控制决策问题 .
短句来源
     By ergodic property of the processes, the solution of the average cost Poisson equation can be viewed as a definition for the concept of Markov performance potential.
     根据系统的遍历性 ,平均代价Poisson方程的解可被看作是性能势的一种定义 .
短句来源
     In this paper, we study optimal policies for a class of continuous time Markov control processes (CTMCPs) with infinite horizon average cost criteria.
     文中研究了一类连续时间Markov控制过程 (CTMCP)无穷水平平均代价性能的最优控制决策问题 .
短句来源
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  average-cost
     By the embedded Markov chain, the problems of optimal stationary policies are studied for controlled M/G/1 queuing systems with the infinite horizon average-cost criteria.
     通过嵌入Markov链的方法,讨论了受控M/G/1排队系统,在无限水平平均代价准则下的最优平稳策略问题。
短句来源
     Optimal Robust Control Policy for Continuous-time Markov Control Processes With Average-Cost Criteria
     连续时间Markov控制过程的平均代价最优鲁棒控制策略
短句来源
     Based on performance potential theorem and Bellman optimality equation, it is easy to establish optimality equation, which we call performance potential-based Bellman optimality equation, for both average-cost and discounted-cost performance criteria.
     基于性能势理论及Bellman最优方程,很容易建立平均代价和折扣代价性能准则下的最优性方程,称之为基于性能势的Bellman最优方程。
短句来源
     Optimization algorithms are studied for a class of continuous-time Markov control processes (CTMCPs) with infinite horizon average-cost criteria and compact action set.
     研究一类连续时间 Markov控制过程 ( CTMCP)在紧致行动集上关于平均代价性能准则的优化算法。
短句来源
     Based on the equivalent Markov process,performance optimization algorithms were studied for a class of semi-Markov control processes (SMCPs) with infinite horizon average-cost criteria and compact action set.
     根据等价Markov过程方法,研究了一类半Markov控制过程在紧致行动集上关于无限水平平均代价准则的性能优化算法.
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  “平均代价”译为未确定词的双语例句
     The average-Poisson equation is defined for infinite horizon average model and the optimality equation is induced in a compact action set.
     定义了平均Poisson方程,导出了平均代价模型在紧致行动集上的最优性方程。
短句来源
     With the critic model of neuro-dynamic programming methodology, we discuss parameterized TD(0) learning rules and parameter-updating formula for both average-criteria and discounted-criteria problems respectively, and derive the NDP optimization algorithms on the basis of TD(0) learning. Then, by simulating a sample path, we introduce the unified TD(0) learning formula of potentials, and develop a unified NDP optimization approach based on parameterized TD(0) learning.
     并分别讨论了平均代价准则和折扣代价准则下MDP优化的参数化TD(0)学习规则和参数改进公式,建立了基于TD(0)学习的Critic模式下的NDP优化算法,另外从性能势在样本轨道上的定义出发,给出了两种性能准则下统一的性能势TD(0)学习公式,以及建立在参数TD(0)学习基础上的统一的NDP优化方法。
短句来源
     Simulation results show that our heuristics achieve good cost performance.
     仿真显示算法取得了良好的平均代价性能 .
短句来源
     We also use simulation to compare DCLC-DSF to the optimal DCLC algorithm CBF and the least-delay path algorithm LDP. The results show that DCLC-DSF path costs are within 5-8% from those of the optimal solution, which proves that DCLC-DSF is a simple, accurate and robust heuristic algorithm.
     仿真实验表明 :DCL C- DSF算法的平均代价不精确度是最佳算法的 5 - 8% ,证明它是一种简单、精确、健壮的启发式算法 .
短句来源
     By one uniformized chain of a MDP and the approximation representation of performance potentials with a neural network, we focus on the critic model of neuro-dynamic programming (NDP) methodology. We derive parameterized TD(0) learning rules and parameter-updating formula for both average criteria and discounted criteria problems, and discuss the potential-based approximate policy iteration algorithms.
     本文通过MDP的一个一致化链和Markov性能势的神经元网络逼近,重点研究了Critic模式下的一种神经元动态规划(NDP)优化方法,给出了用于平均代价准则和折扣代价准则MDP优化的参数化TD(0)学习规则和参数改进公式,并讨论了基于性能势的逼近策略迭代算法。
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  average cost
In previous work, under some assumptions, we specified a replacement rule which minimizes the long-run (expected) average cost per unit time and possesses control limit property.
      
Fur-thermore, the limiting distribution of average cost of a portfolio of increasing life insurance for multiple-life status is studied.
      
Furthermore, the limiting distribution of average cost of this portfolio is discussed with the expression of the limiting distribution under the assumption that the force of interest accumulation is an independent increment process.
      
The average cost in the LMWH group was RMB 1218.60 Yuan and RMB 1541.40 Yuan in the UH group.
      
The average cost of supporting one child (and its family) during 1 year is calculated to be 132 882 Danish Crowns, equal to £ 9280 or US $ 13 436.
      
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  average-cost
In our current study we measure performance in terms of long-run expected average-cost.
      
Our purpose is to minimize the long-run average-cost functional.
      
Our results indicate that, in the long run, the combined effect of regulation and advertising leads to a steady-state equilibrium that is closer to the minimum point on the firm's long-run average-cost curve than the original output level.
      
Thus, an invisible-hand property is established that pushes the regulated firm to shift its demand curve toward the minimum point on its long-run average-cost curve in the presence of regulation.
      
Average-cost Pricing, Increasing Returns, and Optimal Output: Comparing Home and Market Production
      
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In this paper,we study the NP-hard delay-constrained least-cost routing problem.We propose a new framework to solve the problem and provide simple and efficient source routing heuristics from the model,through which one can always find a delay-constrained path if such a path exists.Computation complexity of our heuristics is O(|V|2) and on-line complexity is O(|V|).Simulation results show that our heuristics achieve good cost performance.Finally,we extend the model to routing problem under multiple QoS constraints....

In this paper,we study the NP-hard delay-constrained least-cost routing problem.We propose a new framework to solve the problem and provide simple and efficient source routing heuristics from the model,through which one can always find a delay-constrained path if such a path exists.Computation complexity of our heuristics is O(|V|2) and on-line complexity is O(|V|).Simulation results show that our heuristics achieve good cost performance.Finally,we extend the model to routing problem under multiple QoS constraints.

本文研究了网络路由中的一个NPC问题 :时延受限最小代价路由问题 .文中提出了一个理论框架 ,并给出了多个简单有效的启发式算法 ,在满足给定时延约束条件可行路径存在时 ,算法总能找到满足约束条件的代价优化路径 .文中提出的启发式算法复杂性为O(|V|2 )且在线复杂性为O(|V|) .仿真显示算法取得了良好的平均代价性能 .最后将模型扩展到多QoS限制条件下的路由问题

Delay-constrained least-cost unicast routing problem is NP-Complete. In this paper, we present a distributed heuristic algorithm, called the distributed DCLC unicast routing heuristic based on selection function (DCLC-DSF). DCLC-DSF, which is a dynamic routing algorithm with re-routing and negotiation mechanism, only requires the local information to be kept at each node: the delay and cost of neighbor links. In the worst case, Its message complexity of DCLC-DSF is O(e\+2), and the computation complexity of...

Delay-constrained least-cost unicast routing problem is NP-Complete. In this paper, we present a distributed heuristic algorithm, called the distributed DCLC unicast routing heuristic based on selection function (DCLC-DSF). DCLC-DSF, which is a dynamic routing algorithm with re-routing and negotiation mechanism, only requires the local information to be kept at each node: the delay and cost of neighbor links. In the worst case, Its message complexity of DCLC-DSF is O(e\+2), and the computation complexity of each node is O(n\+2). While for a stable network, the message complexity is O(e). The simulation results also show that, on the average, DCLC-DSF requires much fewer messages. Therefore, DCLC-DSF scales well to large-scale networks. We picture the protocol of DCLC-DSF by a finite state machine. We also use simulation to compare DCLC-DSF to the optimal DCLC algorithm CBF and the least-delay path algorithm LDP. The results show that DCLC-DSF path costs are within 5-8% from those of the optimal solution, which proves that DCLC-DSF is a simple, accurate and robust heuristic algorithm.

Qo S路由的 DCL C单播路由 (Delay- Constrained L east- Cost Unicast Routing)问题属于 NP—完全问题 .本文提出一种多项式复杂度的分布式启发算法 DCL C- DSF.DCL C- DSF基于简单的选择函数 ,每个网络结点只需维持本地的状态信息 :相邻链路的延时和代价度量 .该算法有以下优点 :1)简单性 ;2 )动态性 ;3)重路由功能 ;4)协商功能 .在最坏情况下 ,DCL C- DSF的消息复杂度为 O(e2 ) ,结点的计算复杂度为 O(n2 ) ;在稳定的网络环境下 ,消息复杂度为 O(e) .此外 ,本文还给出 DCL C- DSF算法的有限状态机模型 .仿真实验表明 :DCL C- DSF算法的平均代价不精确度是最佳算法的 5 - 8% ,证明它是一种简单、精确、健壮的启发式算法 .

This paper deals with the performance optimization problem of a class of controlled closed queueing network systems (CQNS). We introduce two fundamental concepts: the discounted cost α-performance potentials and average cost performance potentials, and consider a fundamental relation between the two potentials. Under a general assumption, we establish directly the optimality equation for infinite time horizon average cost model and prove the existence of optimal solution in a compact action set by using properties...

This paper deals with the performance optimization problem of a class of controlled closed queueing network systems (CQNS). We introduce two fundamental concepts: the discounted cost α-performance potentials and average cost performance potentials, and consider a fundamental relation between the two potentials. Under a general assumption, we establish directly the optimality equation for infinite time horizon average cost model and prove the existence of optimal solution in a compact action set by using properties of the performance potentials, suggest an policy_optimality algorithm and give a numerical example to illustrate the application of the proposed algorithm.

研究一类受控闭排队网络系统的性能优化问题 .文章引进了两个基本概念 :折扣代价α 性能势和平均代价性能势 ,并且讨论了这两个性能势之间的一个关系式 .在一般的假设条件下 ,我们应用性能势的基本性质直接建立了无限时间水平平均代价模型的最优性方程 ,并且证明了在紧致集上最优解的存在性 .最后给出了一个策略优化的迭代算法并通过一个实际算例以说明该算法的效果 .

 
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