论文标题
基于新型节点的蝙蝠，以查找所有最小切割
Novel Node-Based BAT for Finding All Minimal Cuts
论文作者
论文摘要
储层计算是预测湍流的有力工具，其简单的架构具有处理大型系统的计算效率。然而，其实现通常需要完整的状态向量测量和系统非线性知识。我们使用非线性投影函数将系统测量扩展到高维空间，然后将其输入到储层中以获得预测。我们展示了这种储层计算网络在时空混沌系统上的应用，该系统模拟了湍流的若干特征。我们表明，使用径向基函数作为非线性投影器，即使只有部分观测并且不知道控制方程，也能稳健地捕捉复杂的系统非线性。最后，我们表明，当测量稀疏、不完整且带有噪声，甚至控制方程变得不准确时，我们的网络仍然可以产生相当准确的预测，从而为实际湍流系统的无模型预测铺平了道路。
The binary-state network, a basic network, and its components are either working or failed. It is fundamental to all types of current networks, such as utility networks (gas, water, electricity, and 4G/5G), the Internet of Things (IoT), social networks, and supply chains. Network reliability is an important index in the planning, design, evaluation, and control of network systems, and the minimal path (MC) is the basis of an MC-based algorithm for calculating reliability. A new BAT called recursive node-based BAT is proposed and implemented in a recursive manner such that the jth vector in the ith iteration is equal to its parent, which is the jth vector, except that its ith coordinate value is one. Based on time complexity analysis and experiments on 20 benchmark binary-state networks, the proposed recursive node-based BAT is more efficient than the best-known node-based algorithm in finding MCs when combined with powerful rules to discard these infeasible vectors and all their offspring.
