论文标题
部分可观测时空混沌系统的无模型预测
Finding the Shape of Lacunae of the Wave Equation Using Artificial Neural Networks
论文作者
论文摘要
我们应用一个完全连接的神经网络来确定波动方程溶液中空隙的形状。空隙是传播波的尾随前部后面的安静区域。使用计算机模拟数据集对网络进行训练，该数据集包含足够数量的样本。然后显示网络可以正确地重建空白的形状，包括完整封闭时的配置。
We apply a fully connected neural network to determine the shape of the lacunae in the solutions of the wave equation. Lacunae are the regions of quietness behind the trailing fronts of the propagating waves. The network is trained using a computer simulated data set containing a sufficiently large number of samples. The network is then shown to correctly reconstruct the shape of lacunae including the configurations when it is fully enclosed.
