Patent ID: 11874429
Assignee: NANJING UNIVERSITY OF INFORMATION SCIENCE AND TECHNOLOGY
Field: Computer technology (Electrical engineering)
Classification: CPC G  Y | IPC G

Claim 2:
3. The high-temperature disaster forecast method based on the directed graph neural network according to claim 1, wherein the temporal convolutional module is composed of four convolution kernels of different sizes and configured to extract time characteristics of data; in a process of extracting the time characteristics of data, a receptive field is controlled by setting sizes of the four convolution kernels; and a calculation formula of the receptive field is as follows:

rfsize=(out−1)*stride+ksize;

where out represents a size of receptive field of an upper layer; stride represents a moving stride of receptive field of current layer and has a default value of 1; and ksize represents a size of convolution kernel of the current layer.