ID 原文 译文
6794 通过状态机学习算法,可以提取传输层安全(transport layer security,TLS)协议的实现库状态机模型来分析其安全性。 By state machine learning algorithm can extract the transport layer security (transport layer security, TLS) implementation of the protocol state machine model to analyze its security.
6795 当前在状态机学习中需要解决状态机学习时间随目标系统状态数增长而呈指数级增长的问题。 The state machines need to be solved in the state machine learning study time along with the state of the target system and increase exponentially.
6796 提出一种改进的状态机学习算法,通过TLS协议特定套接字约简所需测试序列; An improved state machine learning algorithm, through the TLS protocol specific socket reduction required test sequence;
6797 结合检查点算法构造测试序列的前缀树,简化目标系统对测试序列测试步骤。 Combined with checkpoint algorithm test sequence prefix tree structure, simplify the target system of test sequence test steps.
6798 测试结果表明,提出的改进算法能够大幅减少状态机学习过程生成的等价查询数量,加速状态机学习过程。 Test results show that the proposed algorithm can significantly reduce the state machine equivalent number of queries generated by the learning process, to speed up the state machine learning process.
6799 同时通过学习到的状态机模型,分析其异常状态,找到一个OpenSSl的逻辑错误,证明学习到的模型是有效的。 At the same time, by studying the state machine model, analyzes the abnormal state, find a OpenSSl logic errors, prove that learning to model is valid.
6800 针对带模糊时间窗口、模糊运输费用以及模糊运输风险的多目标军事物资运输问题,利用模糊期望理论,建立了带模糊约束问题的多目标运输路径优化模型,并利用改进的多目标量子遗传算法求解该模型。 With fuzzy time window, transportation costs and risks of multi-objective fuzzy transportation of military materials transportation problem, using the theory of fuzzy expectation, established the multi-objective transportation problem with fuzzy constraint of path optimization model, and by using the improved multi-objective quantum genetic algorithm to solve the model.
6801 算法中采用量子比特编码,引入非支配排序和精英保留策略,防止算法陷入局部最优。 Method of using quantum bit coding algorithm, and the introduction of non dominated sorting and elite reserved strategy, prevent algorithm falls into local optimum.
6802 仿真实验结果表明,建立的模型合理、算法有效,在军事物资配送问题中具有一定的实用价值。 The simulation experimental results show that the established model, the algorithm is effective and reasonable in military supplies distribution problem has certain practical value.
6803 与传统的多目标遗传算法相比较,利用改进的多目标量子遗传算法求解该问题,收敛速度更快。 Compared with the traditional multi-objective genetic algorithm, using the improved multi-objective quantum genetic algorithm to solve the problem, the convergence speed is faster.