ID 原文 译文
58038 再引入加权中位数来提高接收信号强度( ＲSSI) 的精度;最后采用重心法进行内点测试减少误判，提高定位精度. Weightedmedian is then used to improve the accuracy of received signal strength indication ( ＲSSI) ，the center ofgravity method is used for interior point testing to reduce misjudgment and improve localization accuracy.
58039 仿真结果表明，混合滤波算法比其他滤波方法处理 ＲSSI 数据的测距精度更高，HFG-APIT 的定位误差分别为最小二乘定位算法( LSM-ＲSSI) 和 APIT 定位算法的 41.7% 和 23.8% ，整体定位性能也优于其他 2 种算法. Simulation results show that the hybrid filtering algorithm has higher ranging accuracy than other filteringmethods in processing ＲSSI data and the localization errors of HFG-APIT are 41. 7% and 23. 8% of ＲSSIlocalization algorithm based on least squares method ( LSM-ＲSSI) and APIT localization algorithm，thelocalization performance is also better than the other two algorithms.
58040 业务流程预测性监控是过程管理的重要内容，已有的研究大部分是基于显式的工作流模型进行预测. The problem of predicting an ongoing business process based on sequence is discussed. Business process predictive monitoring is an important part of process mining.
58041 但是在实际应用中，企业可能并没有对整个过程实施端到端的工作流建模和管理，或者由于权限原因只能够获得部分执行日志，难以基于完整的业务流程模型进行预测，对此，提出了一种基于频繁活动集的序列编码处理日志中的低频活动，并通过搜寻历史相似数据进行预测的方法. Most of the existing research focuses on forecasting based on explicit workflow models. However，the enterprise may not implement endto-end workflow modeling and management for the process，or only own partial execution logs due to permissions. In these cases，it is difficult to make prediction based on the complete process model. This article proposes a frequent activity set based sequence encoding method to handle the low-frequency activities in the log，and performs prediction by searching historical similar data.
58042 该方法能够随着日志的更新适应由于概念漂移导致的模型改变. As the log is updated，the algorithm will adapt to model changes due to the concept drift.
58043 在真实的数据集上进行的实验结果验证了算法的有效性. The algorithm is validated on real data sets.
58044 提出了一种基于图论和有限状态机( FSM) 的统一建模语言( UML) 模型与代码一致性检测方法. A unified modeling language ( UML) model and code consistency checking method based ongraph theory and finite state machine ( FSM) was proposed.
58045 给出了该方法的基本思路;分别讨论了 UML 模型与代码静态一致性检测和动态一致性检测算法;实现了该检测方法的支撑工具，并使用该工具对 C + + 项目 UMLChecker 1.0 进行了检测. The basic idea of this method was given; thestatic consistency checking and the dynamic consistency checking algorithms between UML models andcode were discussed respectively; a support tool for this method was implemented，and C + + projectUMLChecker 1. 0 was checked by using this tool.
58046 实验结果表明，所提方法可对 UML 模型与代码的一致性进行检测，且具有较高的检测精度. The experimental results show that this method cancheck consistency between UML models and code，and has a high checking accuracy.
58047 通过对静态行为和动态行为的一致性检测可知，检测精度明显提升 For consistencychecking in behavioral aspects，checking accuracy rate is improved obviously.