分布式混杂奇异优化算法仿真数据集

该数据在网络攻击作用下，针对有无集合约束的分布式优化问题，结合Matlab和设计的分布式混杂奇异优化算法，给出分布式优化问题在扰动影响下的最优解数据、扰动估计误差数据以及网络攻击所允许的频率和出现的总时间数据。通过攻击和无攻击交替出现的情况，采用Matlab进行编程仿真，并在扰动和网络攻击共同作用下，采集到分布式混杂奇异优化算法辨识有无集合约束优化问题的最优解能力的变化情况。该数据集可为随机网络攻击下分布式优化问题的相关研究提供参考。This dataset targets distributed optimization problems with and without set constraints under network attacks. By leveraging Matlab and the pre-designed distributed hybrid singular optimization algorithm, it provides the optimal solution data of distributed optimization problems under disturbances, disturbance estimation error data, as well as the allowable frequency and total occurrence duration of network attacks. Through Matlab-based programmed simulations with alternating attack and attack-free scenarios, this dataset collects the variations in the performance of the designed distributed hybrid singular optimization algorithm when identifying the optimal solutions of set-constrained and unconstrained optimization problems under the combined effects of disturbances and network attacks. This dataset can serve as a reference for relevant research on distributed optimization problems under stochastic network attacks.

搜集汇总

背景与挑战

背景概述

该数据集针对网络攻击下的分布式优化问题，通过Matlab仿真生成了最优解、扰动估计误差及攻击参数等数据，用于评估分布式混杂奇异优化算法在有无集合约束下的性能。它为随机网络攻击下的分布式优化研究提供了参考。