Matlab-based neural network design, matlab neural network training pictures

Detailed explanation of the five lines of the matlab BP neural network performance graph

The three colored solid lines on the figure are respectively: the performance of the MSE indicator of the BP training process of each generation, the performance of the MSE indicator of the BP cross-validation process of each generation and the MSE indicator performance of the BP test process in each generation.

In particular, one should pay attention to the inner TEST red line, which is the BP calculation/training result. The BEST dotted line indicates that the BP training result is the best when the BP network is trained to the eighth generation.

GOAL The dotted line is the network capacity training stop goal (a) set when programming or directly using MATLAB's ANN toolbox to train this BP.

Extended information: BP (Back Propagation) neural network was proposed in 1986 by a group of scientists led by Rumelhart and McCelland.

BP (Back Propagation) is a multi-layer feedforward network trained by the backpropagation error backpropagation algorithm, and is one of the most widely used neural network models.

The BP network can learn and store a large number of input-output pattern mapping relationships without revealing the mathematical equations describing these mapping relationships in advance.

The learning rule of the BP network is to use the steepest descent method and continuously adjust the weights and thresholds of the network through backpropagation to minimize the sum of squared errors of the network. The topology of BP neural network model includes input layer, hidden layer and output layer.

Google AI Writing Project: Neural Network Pseudo-Original

Three pictures of MATLAB training when doing BP neural network

I can't understand the BP neural network training graph in Matlab, and Mengxin urgently asks for advice from the master.

Please help explain what the four graphs of matlab doing bp neural network regression mean

Hello, I am very happy to answer you. Indicates that when network training is predicted, a simple regression analysis is used, part of the data is used for training, part of the data is used to confirm the training situation, and the remaining data is used for testing, and the final overall situation.

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I am looking for guidance on the training results of BP neural network in Matlab, and I am very grateful to you for your analysis.

P=[1;2;3;4;5];% month P=[P/50]; T=[2;3;4;5;6];% month training sample T=[T/50]; threshold=[0 1;0 1;0 1;0 1;0 1;0 1;0 1];net=newff(threshold,[15,7],{'tansig','logsig'},'trainlm' );net.trainParam.epochs=2000;=0.001;=0.1;net=train(net,P,T);P_test=[June]';%June data forecast July P_test=[P_test/50]; y=sim(net,P_test)y=[y*50].