ID 原文 译文
52767 通过初始稀疏性估计和变步长策略，减少了SAMP中收敛所需的迭代次数。 By incorporating an initial sparsity estimation step and adopting a variable step size strategy, the number of iterations needed for convergence in SAMP can be significantly reduced.
52768 利用真实的地震数据和微电阻率成像数据进行实验，将所提出的方法与压缩感知重建算法进行了比较， Using real seismic data and micro-resistivity imaging data, the proposed novel method is compared with state-of-the-art compressive sensing reconstruction algorithms.
52769 不仅提高了重建数据的准确性，而且缩短了执行时间。 The experimental results show that the accuracy of the reconstructed data is significantly improved, and the execution time is also reduced.
52770 在实际交通数据收集过程中，采集设备故障、维修等问题均易导致采集到的交通数据存在一定的缺失。 In the process of actual traffic data collection, problems such as equipment failure and maintenance are likely to cause traffic data missing.
52771 针对交通数据缺失情况下的交通流预测问题，本文提出了一种基于生成式对抗网络的短时交通流预测模型。 Aiming at the problem of traffic flow prediction with missing data, a short-term traffic flow prediction model based on generative adversarial networks is proposed.
52772 该模型由生成网络和判别网络两部分组成。 The model is composed of two parts:generating network and discriminating network.
52773 其中，生成网络由全连接层和门控循环单元(GRU)构成，以编码-解码的形式完成对未来交通状态的预测输出; The generation network is composed of the fully connected layer and the gated recurrent unit(GRU), which completes the prediction output of the future traffic flow in the form of encoding-decoding;
52774 判别网络由多层全连接层构成，通过Wasserstein距离的计算完成对真假样本的有效判断。 the discriminant network is composed of multiple fully connected layers, which discriminates the real traffic data and fake data by the compute of Wasserstein distance.
52775 实验结果表明，本文提出的模型不仅适用于不同比例数据缺失下的短时交通流预测，而且其预测表现优于其他对比模型。 The experimental results show that the proposed model is not only suitable for short-term traffic flow prediction with different proportions of data missing, but also has a better prediction performance than other comparative models.
52776 在引入移动边缘计算(MEC)技术的超密集网络(UDN)中，网络性能受无线传输链路质量和基站计算资源部署的共同影响。 In mobile edge computing(MEC) enhanced ultra dense networks(MEC), inter-cell interference has become one of the key problems as the small eNBs(SeNBs) are densely deployed.