Patent ID: 11948087
Assignee: HUAZHONG UNIVERSITY OF SCIENCE AND TECHNOLOGY
Field: Computer technology (Electrical engineering)
Classification: CPC G  Y | IPC G

Claim 4:
5. The drop impact prediction method for heavy equipment airdrop based on a neural network according to claim 1, wherein in step S3, said training the BP neural network model by using the data in the training set and accumulated test data, and adjusting network parameters of the BP neural network model comprises:
training a network by using a neural network toolbox in MATLAB:
setting the model to be a neural network which is of a three-layer structure;
setting the number of the nodes on the input layer to be 8, the number of the nodes on the intermediate hidden layer to be 12, and the number of the nodes on the output layer to be 2;
setting the activation functions of the intermediate hidden layer and the output layer to be a tansig function and a logsig function, respectively;
setting a network training function to be traingdx and a network performance function to be mse;
setting network parameters, network iteration epochs, an expected error goal, and a learning rate lr; and
after the parameters are set, substituting the data of the training set to start to train the neural network.