public HybridModel(HybridModelParameter parameter)
: base(parameter)
{
Orgnization = "HUST WREIS";
ID = "34934C27-DD41-44D8-B359-BF56B663A6B8";
Name = "Hybrid Model";
Descriptions = "";
}
public static IForecastingModel CreateForecastingModel(string name)
{
IForecastingModel model = null;
switch (name)
{
case "Artificial Neural Network":
AnnModelParameter annPara = new AnnModelParameter();
model = new NeuralNetworkModel(annPara);
break;
case "HIGANN":
AnnModelParameter annPara1 = new AnnModelParameter();
model = new NeuralNetworkModel(annPara1);
break;
case "Support Vector Machine":
Heiflow.AI.SVM.Parameter p = new Heiflow.AI.SVM.Parameter();
model = new SVMModel(p);
break;
case "Multiple Linear Regression":
ModelParameter mp = new ModelParameter();
model = new MLRModel(mp);
break;
case "Genetic Programming":
GPModelParameter para = new GPModelParameter();
model = new GPModel(para);
break;
case "Model Tree":
Rule root = new Rule(5, 0.47035, RuleType.Interior);
Rule right = new Rule(RuleType.RightLeaf);
root.RightChild = right;
Rule left = new Rule(5, 0.30445, RuleType.Interior);
root.LeftChild = left;
Rule left1 = new Rule(RuleType.LeftLeaf);
left.LeftChild = left1;
Rule right1 = new Rule(9, 0.156, RuleType.Interior);
left.RightChild = right1;
Rule right1_left = new Rule(RuleType.LeftLeaf);
right1.LeftChild = right1_left;
Rule right1_right = new Rule(RuleType.RightLeaf);
right1.RightChild = right1_right;
HybridModelParameter hmp = new HybridModelParameter(root);
model = new HybridModel(hmp);
break;
}
return(model);
}
public override double Forecast(double[] inputVector)
{
HybridModelParameter hmp = mParameter as HybridModelParameter;
MLRModel mlr = hmp.CurrentLeafRule.Model as MLRModel;
if (mlr != null)
{
double y = 0;
for (int i = 0; i < inputVector.Length; i++)
{
y += inputVector[i] * mlr.RegressionCoefficients[i];
}
return(y);
}
else
{
return(0);
}
}
public override void Train(IForecastingDataSets datasets)
{
HybridModelParameter para = mParameter as HybridModelParameter;
OnStartRunning(new ComponentRunEventArgs(datasets));
if (para.Rule.Type == RuleType.Interior)
{
BuildRuleTree(para.Rule, datasets);
datasets.ForecastedData = new double[datasets.InputData.Length][];
for (int i = 0; i < datasets.InputData.Length; i++)
{
datasets.ForecastedData[i] = new double[1];
HybridModelParameter hmp = mParameter as HybridModelParameter;
hmp.CurrentLeafRule = LocateRule(datasets.InputData[i], hmp.Rule);
datasets.ForecastedData[i][0] = Forecast(datasets.InputData[i]);
OnRunningEpoch(new ComponentRunEpochEventArgs(i));
}
}
OnFinishRunning(new ComponentRunEventArgs(datasets));
}
