Question

如何看MATLAB运行神经网络的结果

NEWRB, neurons = 0, SSE = 2.70012

net1 =

Neural Network object:

architecture:

numInputs: 1
numLayers: 2
biasConnect: [1; 1]
inputConnect: [1; 0]
layerConnect: [0 0; 1 0]
outputConnect: [0 1]
targetConnect: [0 0]

numOutputs: 1 (read-only)
numTargets: 0 (read-only)
numInputDelays: 0 (read-only)
numLayerDelays: 0 (read-only)

subobject structures:

inputs: {1x1 cell} of inputs
layers: {2x1 cell} of layers
outputs: {1x2 cell} containing 1 output
targets: {1x2 cell} containing no targets
biases: {2x1 cell} containing 2 biases
inputWeights: {2x1 cell} containing 1 input weight
layerWeights: {2x2 cell} containing 1 layer weight

functions:

adaptFcn: (none)
initFcn: (none)
performFcn: 'mse'
trainFcn: (none)

parameters:

adaptParam: (none)
initParam: (none)
performParam: (none)
trainParam: (none)

weight and bias values:

IW: {2x1 cell} containing 1 input weight matrix
LW: {2x2 cell} containing 1 layer weight matrix
b: {2x1 cell} containing 2 bias vectors

other:

userdata: (user stuff)
y1 =

26.7693

delta1 =

0.1839

Answer 1

如何看MATLAB运行神经网络的结果
从图中Neural Network可以看出，你的网络结构是两个隐含层，2-3-1-1结构的网络，算法是traindm，显示出来的误差变化为均方误差值mse。经过482次迭代循环完成训练，耗时5秒。相同计算精度的话，训练次数越少，耗时越短，网络结构越优秀。达到设定的网络精度0.001的时候，误差下降梯度为0.0046，远大于默认的1e-5，说明此时的网络误差仍在快速下降，所以可以把训练精度目标再提高一些，比如设为0.0001或者1e-5。