网络抗毁性的点韧性度指标计算方法研究
发布时间：2019-05-27 15:34
【摘要】：为快速获取网络点韧性度以衡量其抗毁性性能,设计基于改进二进制粒子群(BPSO)算法的点韧性度计算方法。改进BPSO算法的概率映射函数和位置更新式以解决算法容易陷入局部最优的不足,对网络节点状态进行编码以获取种群粒子,并设计基于广度优先搜索思想的方法求解剩余网络的适应度函数值;最后综合改进BPSO算法和适应度函数求解算法设计点韧性度计算方法。在两种基本网络和两种实际网络中的仿真分析验证了方法的有效性。
[Abstract]:In order to quickly obtain the point toughness of the network to measure its invulnerability, a point toughness calculation method based on the improved binary particle swarm optimization (BPSO) algorithm is designed. The probability mapping function and position of BPSO algorithm are improved to solve the problem that the algorithm is easy to fall into local optimization. The state of network nodes is encoded to obtain the population particles. A method based on the idea of breadth first search is designed to solve the fitness function value of the residual network. Finally, the improved BPSO algorithm and fitness function algorithm are used to design the point toughness calculation method. The simulation results in two basic networks and two practical networks verify the effectiveness of the method.
【作者单位】： 空军工程大学防空反导学院;西京学院理学院;
【基金】：全军军事学研究生课题资助项目
【分类号】：O157.5;TP18
本文编号：2486265
[Abstract]:In order to quickly obtain the point toughness of the network to measure its invulnerability, a point toughness calculation method based on the improved binary particle swarm optimization (BPSO) algorithm is designed. The probability mapping function and position of BPSO algorithm are improved to solve the problem that the algorithm is easy to fall into local optimization. The state of network nodes is encoded to obtain the population particles. A method based on the idea of breadth first search is designed to solve the fitness function value of the residual network. Finally, the improved BPSO algorithm and fitness function algorithm are used to design the point toughness calculation method. The simulation results in two basic networks and two practical networks verify the effectiveness of the method.
【作者单位】： 空军工程大学防空反导学院;西京学院理学院;
【基金】：全军军事学研究生课题资助项目
【分类号】：O157.5;TP18
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