1) optimal weighted Steiner tree
加权Steiner最优树
1.
Ant algorithm for optimal weighted Steiner tree and its application in location allocation based on the concept of electronic potential
在传统欧氏Steiner树的基础上,提出加权Steiner最优树模型,适用于求解必须考虑结点权值情况下的最短路问题。
2) Steiner Minimal Tree
Steiner最优树
3) Minimum steiner tree
最小Steiner树
1.
The minimum Steiner tree problem is one of the NP-hard problems, which has extensive applications in many real-world problem,such as communications network.
最小Steiner树问题是NP难问题,它在通信网络等许多实际问题中有着广泛的应用。
2.
In this algorithm,used directed diffusion(DD)to deliver interest,and used MMAS algorithm to construct a minimum Steiner tree.
该算法采用定向扩散的机制进行兴趣散布;利用MMAS算法构造一个最小Steiner树,源节点的数据发送到构造好的最小Steiner树上,经过融合后传输到sink节点,降低了网络中传输的数据量。
3.
This paper analyses the theoretical basis and realization methods of relational database systems and keyword search technology, proposes content-based similarity calculate method and Minimum Steiner tree based AST query algorithm.
本文对关系数据库系统和关键词查询技术的理论基础和实现方法进行了分析,提出了基于内容的相似度计算方法和基于最小Steiner树求解的AST查询算法。
4) Steiner minimum tree
Steiner最小树
1.
A delay constrained Steiner minimum tree problem in series-parallel graphs;
系列平行图上带时间约束的Steiner最小树问题
5) optimal weight
最优加权
1.
For the difficulty of determining the reliability of each sensor and low precision of observed data,a new fusion method based on supporting matrix and optimal weight is presented.
针对当前多传感器融合过程中,各传感器可靠度估计困难和观测值融合精度低的问题,文中提出一种基于支持度矩阵的最优加权多传感器融合方法,首先建立各传感器之间的相互支持度矩阵,然后对综合支持度高的传感器进行最优加权融合。
2.
Through training and simulating,by means of MATLAB and compared with optimal weight filter method,BP neural network provides better accuracy in retraining white noise.
多传感器含噪声的输出信号序列和目标真值作为样本,用于网络训练,用检验样本对训练后的网络进行检验,并与最优加权滤波方法比较,MATLAB 下的仿真结果表明:BP 网络用于多传感器系统滤波降噪有明显效果。
3.
Through training and simulating,by means of MATLAB and compared with optimal weight filter method,BP neural network provides better accuracy in restraining white noise.
多传感器含噪声的输出信号序列和目标真值作为样本,用于网络训练,用检验样本对训练后的网络进行检验,并与最优加权以及最优加权与递推最小二乘法相结合的滤波方法比较。
6) best weighting
最优加权
1.
This paper brings forward combining these 3 prediction methods after best weighting method,forming a combination prediction method which has the respective advantage of the 3 methods.
提出了最优加权组合预测方法,其精度更高,更适用于对形变监测数据要求高的场合。
补充资料：ST
分子式C9H9N3O2S2，分子量259.19。简名ST，商品名消治龙。白色晶体或结晶粉末。在空气中稳定，遇光变色。熔点200～204℃。难溶于水，溶于丙酮、稀盐酸、氨水和碱溶液。主要用于治溶血性链球菌、脑膜炎球菌、肺炎球菌等感染性疾病。可由2-氨基噻唑与氯化对硝基苯磺酰缩合，再经还原而制得。
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参考词条