Changeset 16394 for trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Physics/FluidDynamics.cs

Timestamp:

12/18/18 11:35:13 (5 years ago)

Author:

gkronber

Message:

#2957: reviewed implementation and made some adjustments.

The "maximum lift of whole aircraft" is only described in the arXiv version of the paper but has been removed in the peer-reviewed version for ESWA. There seems to be an error in the pre-print (x5 and x6 stand for only one variable in the original formula and the ranges for valid values are missing).

I decided to keep the problem and assumed a rather large range to make the problem more interesting for benchmarking purposes. All differences to the published version of the problem instances are described.

File:

• trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Physics/FluidDynamics.cs (modified) (2 diffs)

trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Physics/FluidDynamics.cs

@@ -27 +27 @@
 namespace HeuristicLab.Problems.Instances.DataAnalysis {
   class FluidDynamics : ArtificialRegressionDataDescriptor {
-    public override string Name { get { return "Flow psi = x1*x2*x5*(1 - x4²/x5²) + 1/(2*Pi) * x3*log(x5/x4)"; } }
+    public override string Name { get { return "Flow Psi = V_inf r sin(th) (1 - R²/r²) + G/(2 π) ln(r/R)"; } }
 
     public override string Description {
       get {
-        return "A full description of this problem instance is given in the paper: A multilevel block building algorithm for fast modeling generalized separable systems. " + Environment.NewLine +
-               "Authors: Chen Chen, Changtong Luo, Zonglin Jiang" + Environment.NewLine +
-               "Function: f(X) = x1*x2*x5*(1 - x4²/x5²) + 1/(2*Pi) * x3*log(x5/x4)" + Environment.NewLine +
-               "with x1 in [60,65], x2 in [30, 40], x3 in [5,10], x4 in [0.5,0.8], x5 in [0.2,0.5]";
+        return "A full description of this problem instance is given in: " + Environment.NewLine +
+          "Chen Chen, Changtong Luo, Zonglin Jiang, \"A multilevel block building algorithm for fast " +
+          "modeling generalized separable systems\", Expert Systems with Applications, Volume 109, 2018, " +
+          "Pages 25-34 https://doi.org/10.1016/j.eswa.2018.05.021. " + Environment.NewLine +
+          "Function: Psi = V_inf r sin(th) (1 - R²/r²) + G/(2 π) ln(r/R)" + Environment.NewLine +
+          "with V_inf ∈ [60 m/s, 65 m/s]," + Environment.NewLine +
+          "th ∈ [30°, 40°]," + Environment.NewLine +
+          "r ∈ [0.2m, 0.5m]," + Environment.NewLine +
+          "R ∈ [0.5m, 0.8m]," + Environment.NewLine +
+          "G ∈ [5 m²/s, 10 m²/s]";
       }
     }
 
-    protected override string TargetVariable { get { return "f(X)"; } }
-    protected override string[] VariableNames { get { return new string[] { "x1", "x2", "x3", "x4", "x5", "f(X)" }; } }
-    protected override string[] AllowedInputVariables { get { return new string[] { "x1", "x2", "x3", "x4", "x5" }; } }
+    protected override string TargetVariable { get { return "Psi"; } }
+    protected override string[] VariableNames { get { return new string[] { "V_inf", "th", "r", "R", "G", "Psi" }; } }
+    protected override string[] AllowedInputVariables { get { return new string[] { "V_inf", "th", "r", "R", "G" }; } }
     protected override int TrainingPartitionStart { get { return 0; } }
     protected override int TrainingPartitionEnd { get { return 100; } }
@@ -58 +64 @@
 
       List<List<double>> data = new List<List<double>>();
-      var x1 = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 60.0, 65.0).ToList();
-      var x2 = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 30.0, 40.0).ToList();
-      var x3 = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 5.0, 10.0).ToList();
-      var x4 = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 0.5, 0.8).ToList();
-      var x5 = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 0.2, 0.5).ToList();
+      var V_inf = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 60.0, 65.0).ToList();
+      var th = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 30.0, 40.0).ToList();
+      var r = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 0.2, 0.5).ToList();
+      var R = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 0.5, 0.8).ToList();
+      var G = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 5, 10).ToList();
 
-      List<double> fx = new List<double>();
-      data.Add(x1);
-      data.Add(x2);
-      data.Add(x3);
-      data.Add(x4);
-      data.Add(x5);
-      data.Add(fx);
+      List<double> Psi = new List<double>();
+      data.Add(V_inf);
+      data.Add(th);
+      data.Add(r);
+      data.Add(R);
+      data.Add(G);
+      data.Add(Psi);
 
-      for (int i = 0; i < x1.Count; i++) {
-        double fxi = x1[i] * x2[i] * x5[i] * (1 - (x4[i] * x4[i]) / (x5[i] * x5[i])) +
-                     (1 / (2 * Math.PI)) * x3[i] * Math.Log(x5[i] / x4[i]);
-        fx.Add(fxi);
+      for (int i = 0; i < V_inf.Count; i++) {
+        var th_rad = Math.PI * th[i] / 180.0;
+        double Psi_i = V_inf[i] * r[i] * Math.Sin(th_rad) * (1 - (R[i] * R[i]) / (r[i] * r[i])) +
+                     (G[i] / (2 * Math.PI)) * Math.Log(r[i] / R[i]);
+        Psi.Add(Psi_i);
       }