ID 原文 译文
44786 最后采用神经网络作为分类器并在识别阶段引入拒识类。 Finally, the neural network was applied as classifier and the reject class was introduced in the banknote recognition.
44787 实验结果表明所提的算法不仅取得了较高的识别率，而且还能够满足纸币清分系统的实时性要求。 The experimental results illustrate that the proposed algorithm obtains high recognition rate and meets the real-time requirement of the banknote recognition system.
44788 复杂战场环境增加了侦察信息处理的不确定性，基于信度函数研究不确定信息尤其是冲突证据度量问题， The complex battlefield environment increases the uncertainty of reconnaissance information processing, so the uncertain information processing is investigated, especially the conflict evidence measurement, based on the belief functions.
44789 提出用归一化的证据相关作为冲突证据度量的相关系数， The normalized evidence correlation is defined as the correlation coefficient measurement for conflict evidence.
44790 针对现有冲突证据度量方法未分清证据单类命题与多类命题的缺点，分别定义并核关系矩阵与核关系矩阵修正并核相关与核相关，得到修正后的冲突证据度量。 In order to solve the drawback that the existing conflict evidence measurement methods do not distinguish the single set and multiple sets, the union core and core relational matrix are defined to modify the union core and core correlation respectively and further obtain the modified conflict evidence measurement.
44791 结合经典的冲突证据算例验证了该冲突证据相关系数度量方法的有效性。 Finally, the efficiency of the proposed correlation coefficient measurement for conflict evidence is illustrated in the classical simulation example.
44792 在智能交通、多任务协作等领域，用着色瓶颈旅行商问题(CBTSP，colored bottleneck traveling salesman problem)所构建模型尺度易趋向于大规模，因此有必要研究大规模 CBTSP 及其求解算法。 In the fields such as intelligent transport and multiple tasks cooperation, the model scale constructed by colored bottleneck traveling salesman problem (CBTSP) tends to large scale, and therefore it is necessary to study the large scale CBTSP and its algorithms.
44793 本文将一种改进蜂群算法(IABC，improved artificial bee colony algorithm)应用于求解大规模 CBTSP。 An improved artificial bee colony algorithm (IABC) was applied to solve the large scale CBTSP.
44794 IABC 首先运用 m-tour 编码方法生成问题的解，然后使用产生邻近解(GNS，generate neighboring solution)优化蜂群算法求解该问题， IABC employed generating neighboring solution (GNS) to improve artificial bee colony algorithm for CBTSP.
44795 GNS 通过采用删除和重插入操作来产生新的解，并在该过程中实现对已有解的优化。 GNS generated new solution by deletion and reinsertion operations, during this process, and it can optimized the existed solution for this problem.