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optimal parameter value
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  “optimal parameter value”译为未确定词的双语例句
     The experimental results show that the optimal parameter value gained by this method makes fuzzy extension matrix obtaining the best classification result.
     实验结果证明,利用遗传算法得到的参数较优,可以使模糊扩张矩阵的分类结果达到较好。
短句来源
     After comparing and analysing two methods for automatic selection of an optimal parameter value,which are a straightforward method and a hierarchical method,heuristic strategy for determining parameter of neighbors in practice has been concluded.
     通过对两种自动选取最佳参数值的方法,即简单方法和分层方法进行试验比较与分析,归纳出在实践中确定邻域参数的启发式策略。
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  相似匹配句对
     Optimal Estimation of Multi - parameter
     多参数最优估计
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     It concluded that the optimal parameter representation for R and K.
     给出了雨侵蚀力指标 R和土壤可蚀性因子 K的计算式 .
短句来源
     Finally, optimal parameter values for the reflection model are obtained.
     最后得到了物体表面反射模型的最优参数.
短句来源
     and b was empirical parameter.
     b为经验常数。
短句来源
     Optimal temperature for D.
     各种光强下的暗呼吸速率均随温度升高而增大。
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  optimal parameter value
The search algorithm for optimal parameter value as employed with a computer is developed.
      
Vt1= Vt1(α), a procedure is proposed that allows us to find the optimal parameter value, α = α0.
      
Two parameters are interdependent if changing the value of one of them impacts the optimal parameter value of the other.
      
Its probability density function is Gaussian, centered on the true optimal parameter value.
      


The Locally Linear Embedding(LLE) algorithm is an effective technique for nonlinear dimensionality reduction of high-dimensional data.It has low time-complexity and strong ability to express manifold.Compared with other dimensionality reduction algorithms,the advantage of the locally linear embedding algorithm is only defining unique parameter: number of nearest neighbors.Performance of algorithm mainly depends on selection of parameter of neighbors.Then one question which is how to select an optimal parameter...

The Locally Linear Embedding(LLE) algorithm is an effective technique for nonlinear dimensionality reduction of high-dimensional data.It has low time-complexity and strong ability to express manifold.Compared with other dimensionality reduction algorithms,the advantage of the locally linear embedding algorithm is only defining unique parameter: number of nearest neighbors.Performance of algorithm mainly depends on selection of parameter of neighbors.Then one question which is how to select an optimal parameter value of neighbors emerges.After comparing and analysing two methods for automatic selection of an optimal parameter value,which are a straightforward method and a hierarchical method,heuristic strategy for determining parameter of neighbors in practice has been concluded.

局部线性嵌入(LLE)算法是有效的非线性降维方法,时间复杂度低并具有强的流形表达能力。与其他降维方法相比,局部线性嵌入算法的优势在于只定义唯一的参数,即邻域数。因此算法的性能主要依靠此邻域参数的选取,这就产生问题:怎样选取邻域参数的最佳值。通过对两种自动选取最佳参数值的方法,即简单方法和分层方法进行试验比较与分析,归纳出在实践中确定邻域参数的启发式策略。

>=To improve the transportation efficiency on the communication networks, a new routing strategy was proposed. Instead of using the routing strategy for shortest path, we give a generalized routing algorithm to find the so-called efficient path, which considers the possible congestion in the nodes along actual paths. Since the nodes with largest degree are very susceptible to traffic congestion, an effective way to improve traffic and control congestion, as our new strategy, can be as redistributing traffic...

>=To improve the transportation efficiency on the communication networks, a new routing strategy was proposed. Instead of using the routing strategy for shortest path, we give a generalized routing algorithm to find the so-called efficient path, which considers the possible congestion in the nodes along actual paths. Since the nodes with largest degree are very susceptible to traffic congestion, an effective way to improve traffic and control congestion, as our new strategy, can be as redistributing traffic load in central nodes to other non-central nodes. Simulation results indicate that the network capability in processing traffic is improved more than 10 times by optimizing the efficient path, which is in good agreement with the analysis.[1] Furthermore, a packet routing strategy with a tunable parameter α based on the local structural information of a scale-free network was proposed and investigated. As free traffic flow on the communication networks is a key to their normal and efficient functioning, we focus on the network capacity that can be measured by the critical point of phase transition from free flow to congestion. Simulations show that the maximal capacity corresponds to α ≈ -1 in the case of identical nodes' delivering ability. To explain this, we investigate the number of packets of each node depending on its degree in the free flow state and observe the power law behavior. Other dynamic properties including average packets traveling time and traffic load are also studied. Inspiringly, our results indicate that some fundamental relationships exist between the dynamics of synchronization and traffic on the scale-free networks. [2, 3] The above local routing protocol can also be generalized to the next-nearest-neighbor search strategy case. It is found that by tuning the parameter a, the scale-free network capacity measured by the order parameter is considerably enhanced compared to the normal next-nearest-neighbor strategy. Due to the low cost of acquiring next-nearest-neighbor information and the strongly improved network capacity, our strategy may be useful for the protocol designing of modern communication networks. [4] The efficiency of traffic routing on communication networks should be reflected by two key measurements, i.e., the network capacity and the average travel time of data packets. We propose furthermore a mixing routing strategy by integrating local static and dynamic information for enhancing the efficiency of traffic on scale-free networks. The strategy is governed by a single parameter. Simulation results show that maximizing the network capacity and reducing the packet travel time can generate an optimal parameter value. Compared with the strategy of adopting exclusive local static information, the new strategy shows its advantages in improving the efficiency of the system. The detailed analysis of the mixing strategy is provided for explaining its effects on traffic routing. The work indicates that

为了改进通讯网络上的传输效率,我们提出几种新的路由策略的建议。为了研究信息包在网络中的传输动力学,我们假定整个网络中在单位时间内有R个信息包产生,并需要从其发源地传送到目的地,发源地和产生地都是随机选取的,但一经选定,即不再改变。只要信息包未到达其目的地,就始终在网络内游荡。每一个结点既是产生信息和接收信息的服务器终端,又是中介传送信息的路由器。我们假定每一个结点送出信息包的速率是一个有限常数C。当一个结点处等待送出的信息包数目超过这一常数C,则未被送出的信息包就要在该结点处排队等候,只能够在下一个时步按照先进先出的原则发送。为了避免信息包在同一路径中不断重复游荡而大大降低传输效率,我们也规定一个信息包将避免重复地走同一个路径,这称为路径重复避免规则。当信息产生速率超过某一临界阈值RC,在网络中排队等候传送的信息包数目就会越来越多地积累,而导致信息传输的交通拥堵。通讯网络的功能要求信息包在网络中的传输始终处于自由状态, 即不发生交通拥堵,因此,临界的产生信息速率RC,即是整个网络处理通讯能力的度量。对于结点连接度分布为幂函数律的无尺度网络,可以证明取最短路径的路由策略一定不是一种好策略。因为在连接度大的中枢结...

为了改进通讯网络上的传输效率,我们提出几种新的路由策略的建议。为了研究信息包在网络中的传输动力学,我们假定整个网络中在单位时间内有R个信息包产生,并需要从其发源地传送到目的地,发源地和产生地都是随机选取的,但一经选定,即不再改变。只要信息包未到达其目的地,就始终在网络内游荡。每一个结点既是产生信息和接收信息的服务器终端,又是中介传送信息的路由器。我们假定每一个结点送出信息包的速率是一个有限常数C。当一个结点处等待送出的信息包数目超过这一常数C,则未被送出的信息包就要在该结点处排队等候,只能够在下一个时步按照先进先出的原则发送。为了避免信息包在同一路径中不断重复游荡而大大降低传输效率,我们也规定一个信息包将避免重复地走同一个路径,这称为路径重复避免规则。当信息产生速率超过某一临界阈值RC,在网络中排队等候传送的信息包数目就会越来越多地积累,而导致信息传输的交通拥堵。通讯网络的功能要求信息包在网络中的传输始终处于自由状态, 即不发生交通拥堵,因此,临界的产生信息速率RC,即是整个网络处理通讯能力的度量。对于结点连接度分布为幂函数律的无尺度网络,可以证明取最短路径的路由策略一定不是一种好策略。因为在连接度大的中枢结点(hub)处,最容易发生交通堵塞,而导致网络通讯能力RC的下降。

 
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