ID 原文 译文
4053 最后，通过分析防守信道的信道容量来衡量系统防守能力，其防守信道的最大互信息量就是入侵检测系统的防守极限能力，其对应的策略分布就是系统的防守能力最佳响应策略。 Finally, the defensive capability of the system was measured by analyzing the channelcapacity of the defensive channel, the maximum mutual information of the defensive channel was the defensive limit capa-bility of the IDS, and the corresponding strategy distribution was the optimal response strategy of the defensive capability of the system.
4054 实验结果表明，所提方案能够有效地降低系统误警和漏警所造成损失。 The experimental results show that the scheme can effectively reduce the loss caused by FPs and FNs.
4055 为了提高异构网络的能量效率和参数摄动抑制能力，减小跨层干扰，提出了一种基于能量效率最大的异构非正交多址接入网络稳健资源分配算法。 In order to improve the suppression capability of parametric perturbation and energy efficiency (EE) of hete-rogeneous networks (HetNets), a robust resource allocation algorithm was proposed to maximize system EE for reducingcross-tier interference power in non-orthogonal multiple access (NOMA) based HetNets.
4056 首先，考虑宏用户干扰功率约束、小蜂窝基站功率约束、资源块分配约束及小蜂窝用户服务质量约束，将资源优化问题建模为混合整数非线性分式规划问题。 Firstly, the resource optimiza-tion problem was formulated as a mixed integer and nonlinear programming one under the constraints of the interferencepower of macrocell users, maximum transmit power of small cell base station (BS), resource block assignment and thequality of service (QoS) requirement of each small cell user.
4057 其次，考虑椭球有界信道不确定模型，利用凸松弛法、Dinkelbach 法和连续凸近似法，将原问题转化为等价的凸优化形式，并利用拉格朗日对偶方法获得解析解。 Then, based on ellipsoid bounded channel uncertainty mod-els, the original problem was converted into the equivalent convex optimization problem by using the convex relaxationmethod, Dinkelbach method and the successive convex approximation (SCA) method. The analytical solutions were ob-tained by using the Lagrangian dual approach.
4058 仿真结果表明，与完美 CSI 算法相比，所提算法具有较好的能效和稳健性。 Simulation results verifiy that the proposed algorithm had better EE androbustness by comparing it with the existing algorithm under perfect channel state information.
4059 针对移动边缘计算环境下，爆炸式增长的物联网智能移动终端处理计算密集型和时延敏感型新兴移动应用时，面临的高时延、高能耗和低可靠性等问题，提出综合考虑时延和能耗的卸载决策模型和基于信誉值的计算资源博弈分配模型， Aiming at the problem of high-latency, high-energy-consumption, and low-reliability mobile caused by com-puting-intensive and delay-sensitive emerging mobile applications in the explosive growth of IoT smart mobile terminalsin the mobile edge computing environment, an offload decision-making model where delay and energy consumption were comprehensively included, and a computing resource game allocation model based on reputation that took into accountwas proposed,
4060 并分别利用改进粒子群算法和拉格朗日乘数法求解。 then improved particle swarm algorithm and the method of Lagrange multipliers were used respectively to solve models.
4061 仿真结果表明，所提方法可满足新兴智能应用对于低时延、低能耗和高可靠性的服务需求，可有效实现计算卸载资源的整体优化配置。 Simulation results show that the proposed method can meet the service requirements of emerging intelli-gent applications for low latency, low energy consumption and high reliability, and effectively implement the overall op-timized allocation of computing offload resources.
4062 为了改善 GPCR 协议中的局部最优、路由环路及在稀疏网络中性能不佳等问题，提出了一种基于权重选择的 GPCR（W-GPCR）协议。 To improve the performance in sparse networks, local optimum, and routing loop in the greedy perimetercoordinator routing (GPCR) protocol, the weighted-GPCR (W-GPCR) protocol was proposed.