算法选择的英文

• algorithm selection

• 算法    algorithm
• 选择    pick and choose; select
• 非法选择    default option
• 测试方法选择    tms testing method select
• 延迟融资办法选择    deferred drawdown option
• 路径选择算法    routing algorithm
• 路由选择算法    routing algorithm
• 任选路径选择算法    optional routing algorithm
• 容错路径选择算法    fault-tolerant routing algorithm
• 二甲基氨基醋酸钾法选择性吸收酸性气过程    alkazid dik process
• 距离向量路由选择算法    distance vector routing algorithm
• 连接状态路由选择算法    link-state routing algorithm
• 链接状态路由选择算法    link state routing algorithm
• 自适应路径选择算法    adaptive routing algorithm
• 沉淀法选矿    levigation
• 干法选煤    dry coal preparation
• 湿法选矿    wet dressing; wet-mill concentration
• 湿法选矿厂    wet-milling plant

• The prior information of pixel intense distribution is introduced . then simulated annealing algorithm is applied to choose the proper neighborhood structure , and the optimal estimate can be obtained
  引入像素强度的先验概率分布模型，运用模拟退火算法选择合适的邻域结构，获得强度的最优估计。
• This paper surveys the development of the multi - user detector as well as new techniques used in this field . after two kinds of typical and basic algorithms , we introduce the performance index to measure the multi - user detector and the principle used to choose the mud algorithm
  在综述了多用户检测技术的发展状况及其一些新技术在该领域内的发展的基础上，本文分析了两种典型的基本算法，讨论了多用户检测算法的性能测度标准和算法选择原则。
• This thesis is focused on the study of data - mining technique in the intelligent decision - making auxiliary system . a data - mining system based on the in - situ investigating information and the in - situ analyzing and testing data is designed and realized . in order to manage the system and select the proper algorithm , an illustration table of the algorithm and a rule - selecting database of the algorithm are proposed in the model management of this system
  本文重点研究了智能辅助决策系统中的数据挖掘技术，设计并实现了现场调查信息和分析测试信息下的数据挖掘系统，在该系统的模型管理中，提出了算法说明表和算法选择规则库，用于算法的管理和选择。
• But it is n ' t ideal because it is fallible in solving down - to - earth questions . for example , it is easy for the system to fall into local optimization state when learning algorithm is unsuitable . furthermore , there is a conflict between the complexity of network and generalization ability
  而神经网络具有一些独特的优点，如非线性映射、容错能力等，因而相对于其它方法，神经网络在数据挖掘中具有更大的前景，但神经网络也存在一些问题，比较典型的包括在学习算法选择不当时，系统易陷于局部极优状态，网络的复杂度与泛化能力之间存在矛盾等等。
• It follows that the description of characteristics of g programming language in labview and the process of building virtual instruments . the paper provides a new spectrum analyzing method of the combination of spread spectrum with fft . at last it gives the arithmetic realization and programming diagram of every part of spectrum monitoring and signal searching
  介绍了labview下如何通过计算机接口获取数据的过程，数据采集过程中各个参数的算法选择；同时阐述了labview平台下g语言的特点及构建虚拟仪器的过程，然后介绍了信号分析处理部分采用的频率扩展与fft相结合的频域分析方法；频谱监测部分各个模块的算法实现；最后给出了信号搜索部分的算法实现及其原理框图。
• On the basis of research on market efficiency , index funding , clustering algorithm and time factor , 295 stocks in shenzhen stock market are selected as the research objects . clustering algorithm with time factor is applied to choose portfolio population , and then single index model is used to calculate the weight of every individual stock in order to construct an index proxy portfolio to track shenzhen composite index
  本文在对市场有效性、指数化投资、聚类算法和时间因子等有关理论进行分析研究的基础上，以在深圳证券交易所上市的295只股票为研究对象，使用加入时间因子的聚类算法选择证券投资群体，再利用单指数法构造市场指数代理证券组合，以此来逼近深圳综合指数。
• This algorithm adopts a middle ground between centroid - base and all - points - based approaches . instead of using a single centroid or all points to represent a cluster , a fixed number of representative points in space are chosen , these points represent and capture the geometry and shape of the cluster . in addition . the representative points of a cluster are generated by first selecting well - scattered objects for the cluster and then " shrinking " or moving them toward the cluster center by a specified fraction , or shrinking factor . the shrinking helps dampen the effects of outliers . therefore , cure is more robust to outliers
  该算法选择基于质心利基于代表对象方法之间的中间策略，它不用单个质心或簇中全部对象米代表一个簇，而是选择数据空间中定数目的只有代表性的点，这些点代表和捕捉到了簇的形状。此外，由于引入了收缩因子使代表点向簇小心“收缩”而使该算法能够较好地消除孤立点的影响，在处理孤立点上也更加健壮。
• At the same time , this paper puts forward a validity function for judging clustering in order to lead us to use it in k - nearest neighbor classification ; then introduces " generalization capability of a case " to k - nearest neighbour . according to the proposed approach , the cases with better generalization capability are maintained as the representative cases while those redundant cases found in their coverage are removed . we can find a new less but almost complete training data set , consequently reduce complexity of seeking near neighbour
  针对k值的学习，本文初步使用了遗传算法选择较优的k值，同时总结了一种聚类有效性函数，数值实验证实了其有效性，旨在指导应用于k -近邻分类中；然后还将“扩张能力”的概念引入k -近邻算法，根据训练集例子不同的覆盖能力，删除冗余样本，得到数量较小同时代表类别情况又比较完全的新的训练集，从而降低查找近邻复杂性。