这是我的源代码，我想减少可能的错误。运行此代码时，经过训练的输出与目标之间存在很大差异。我尝试了不同的方法，但没有奏效，所以请帮我减少它。
a=[31 9333 2000;31 9500 1500;31 9700 2300;31 9700 2320;31 9120 2230;31 9830 2420;31 9300 2900;31 9400 2500]'
g=[35000;23000;3443;2343;1244;9483;4638;4739]'
h=[31 9333 2000]'
inputs =(a);
targets =[g];
% Create a Fitting Network
hiddenLayerSize = 1;
net = fitnet(hiddenLayerSize);
% Choose Input and Output Pre/Post-Processing Functions
% For a list of all processing functions type: help nnprocess
net.inputs{1}.processFcns = {'removeconstantrows','mapminmax'};
net.outputs{2}.processFcns = {'removeconstantrows','mapminmax'};
% Setup Division of Data for Training, Validation, Testing
% For a list of all data division functions type: help nndivide
net.divideFcn = 'dividerand'; % Divide data randomly
net.divideMode = 'sample'; % Divide up every sample
net.divideParam.trainRatio = 70/100;
net.divideParam.valRatio = 15/100;
net.divideParam.testRatio = 15/100;
% For help on training function 'trainlm' type: help trainlm
% For a list of all training functions type: help nntrain
net.trainFcn = 'trainlm'; % Levenberg-Marquardt
% Choose a Performance Function
% For a list of all performance functions type: help nnperformance
net.performFcn = 'mse'; % Mean squared error
% Choose Plot Functions
% For a list of all plot functions type: help nnplot
net.plotFcns = {'plotperform','plottrainstate','ploterrhist', ...
'plotregression','plotconfusion' 'plotfit','plotroc'};
% Train the Network
[net,tr] = train(net,inputs,targets);
plottrainstate(tr)
% Test the Network
outputs = net(inputs)
errors = gsubtract(targets,outputs)
fprintf('errors = %4.3f\t',errors);
performance = perform(net,targets,outputs);
% Recalculate Training, Validation and Test Performance
trainTargets = targets .* tr.trainMask{1};
valTargets = targets .* tr.valMask{1};
testTargets = targets .* tr.testMask{1};
trainPerformance = perform(net,trainTargets,outputs);
valPerformance = perform(net,valTargets,outputs);
testPerformance = perform(net,testTargets,outputs);
% View the Network
view(net);
sc=sim(net,h)