ID 原文 译文
25965 实验证明，本文所提的方法在处理不同目标的优化问题时普适性提高，并在平衡种群的收敛性和多样性上取得显著效果。 The experimental results demonstrate that the proposed method improves the versatility in solving different objectives of optimization problems, and achieves significant effects in balancing convergence and diversity．
25966 在采用无线通信接入的配电网中，入侵检测系统(IDS)通过分析通信网中传输数据来判断入侵事件。 In an electric power distribution grid using wireless communication access, IDS is used to decide system the intrusive event through analyzing the network transmission data．
25967 为提高检测的准确性，本文将深度学习理论应用于 IDS，提出了一种面向配电网无线通信网络新型入侵检测系统，由带有门控循环单元、多层感知器和 Softmax 的循环神经网络组成。 In this paper, to improve the detection accuracy, a deep learning theory is studied for the IDS in the wireless communication network of a power distribution grid． The proposed Ｒecurrent Neural Network (ＲNN) model is composed of Gated Ｒecurrent Unit(GＲU), Multi-Layer Perceptron (MLP) and Softmax．
25968 攻击测试基准实验结果表明 IDS 防御的有效性，在KDD99 测试数据集上，其误报率为 0． 06% ，总检出率为 96． 43% ;在 NSL-KDD 测试数据集上，其误报率低至 0． 86% ，总检出率则为 99． 33% 。 The experimental results on the attack testing baseline demonstrate the effectiveness of the IDS defenses. In the KDD99 test data, its negative error rate and accuracy are with 0． 06% and 96． 43% , and in the NSL-KDD test data, those statistics are 0． 86% with 99． 33% , respectively．
25969 直接判决(DD，Decision-Directed)算法结构简单、音乐噪声抑制能力较好，是当前语音增强领域最为常用的先验信噪比估计方法。 Due to the low computational complexity and acceptable ability in reducing musical noise effect, the decision-directed (DD) approach is widely used for estimating the a priori signal-noise-ratio (SNＲ) in many speechenhancement systems．
25970 但该算法对于滑动因子的选取数值较为敏感，且估计性能要受到时延问题的限定。 However, the DD approach suffers from the problem of time delay and the performance is very sensitive to the fixed smoothing factor．
25971 本文首先采用实际的语音和噪声数据，根据音乐噪声残留及输出语音失真两方面的评测标准对 DD 算法中滑动因子的取值问题进行了研究，通过数据分析给出了其较为明确的上下边界值; Firstly, the performance of DD approach in musical noise reduction as well as speech distortion attenuation are analyzed using actual speech and noise data, and the boundary values of smoothing factors are presented in view of the analyzed results.
25972 然后基于语音及噪声信号的复高斯分布模型，采用软判决技术对两个具有不同滑动因子的 DD 算法进行概率耦合，提出了一种具有双 DD 结构的先验信噪比估计算法。 Then, a novel algorithm is proposed, in which two DD approaches with different smoothing factors are probabilistically combined in an attempt to put together the best properties of them．
25973 该算法可以充分结合两个具有不同特性 DD 算法的优点，在音乐噪声抑制及限制语音失真等方面均获得了较为理想的输出效果。 The contribution of either DD approach to the combination is automatically adjusted in accordance with the speech absence probability, which can be computed using the complex Gaussian model and soft decision technique．
25974 多种噪声背景及输入信噪比条件下的仿真结果表明，相对于目前流行的几种先验信噪比估计算法，本文提出算法具有更为优良的估计性能。 Experiments are carried out in different noise and in-put SNＲ conditions，and the results demonstrate that the proposed algorithm can significantly outperform the popular methods for estimating the a priori SNＲ．