ID 原文 译文
22025 增加差异性势必会降低平均精度，增大平均精度一定会减小差异性。 The increase of diversity among base classifiers will lead to the decrease of the average accuracy, and vice versa.
22026 故在差异性和平均精度之间存在一个平衡状态，使得集成性能最优。 So there exists a tradeoff between the diversity and the average accuracy, which makes the ensemble perform the best with respect to ensemble pruning.
22027 为了寻找该平衡状态，该文提出融合改进二元萤火虫算法和互补性测度的集成剪枝方法。 To find the tradeoff, Improved Binary Glowworm Swarm Optimization combined with Complementarity measure for Ensemble Pruning (IBGSOCEP) is proposed.
22028 首先，采用 bootstrap 抽样方法独立训练出多个基分类器，构建原始基分类器池。 Firstly, an initial pool of classifiers is constructed through training independently some base classifiers using bootstrap sampling.
22029 其次，采用互补性测度对原始基分类器池进行预剪枝。 Secondly, the classifiers in the initial pool are pre-pruned using complementarity measure.
22030 接着，通过改进萤火虫的移动方式和搜索过程，引入重新初始化机制和跳跃行为，提出改进二元萤火虫算法。 Thirdly, Improved Binary Glowworm Swarm Optimization (IBGSO) is proposed by improving moving way, searching processes of glowworm, introducing re-initialization, and leaping behaviors.
22031 最后，采用改进二元萤火虫算法对预剪枝后的基分类器，进行进一步剪枝，选择出集成性能最优的基分类器子集合。 Finally, the optimal sub-ensemble is achieved from the base classifiers after pre-pruning using IBGSO.
22032 在 5 个 UCI 数据集上的实验结果表明，较其他方法，使用较少的基分类器，获得了更优的集成性能，具有良好的有效性和显著性。 Experimental results on 5 UCI datasets demonstrate that IBGSODSEN can achieve better results than other approaches with less number of base classifiers, and that its effectiveness and significance.
22033 针对无线传感器网络(WSNs)日益增大的干扰导致网络容量下降的问题，同时考虑到网络能量有限性，该文综合网络容量和链路传输能耗，构建了高容量低传输能耗的功率控制与信道分配联合博弈模型，并通过理论分析证明该模型存在最优功率和最优信道。 To solve the problem that the network capacity decreases with the increasing interference in Wireless Sensor Networks (WSNs), a joint power control and channel allocation optimization game model is constructed, which considers the limitation of network energy. This game model contains the network capacity and the energy consumption of data transmission in the network. Theoretical analysis proves the existence of the optimal power and the optimal channel.
22034 继而采用最佳响应策略，在该博弈模型基础上提出了一种功率控制与信道分配联合优化算法(PCOA)，理论证明其能收敛到纳什均衡状态，且具有较小的信息复杂度。 Based on the model, a joint Power control and Channel allocation Optimization Algorithm for wireless sensor networks (PCOA) is proposed, which adopts the best response strategy. The theoretical analysis proves that this algorithm can converge to Nash Equilibrium. Besides, the information complexity of this algorithm is small.