source: trunk/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/Physics/AircraftLift.cs @ 16264

Last change on this file since 16264 was 16264, checked in by gkronber, 11 months ago

#2957: initial import of physics problems implemented by lkammere

File size: 3.7 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
4 *
5 * This file is part of HeuristicLab.
6 *
7 * HeuristicLab is free software: you can redistribute it and/or modify
8 * it under the terms of the GNU General Public License as published by
9 * the Free Software Foundation, either version 3 of the License, or
10 * (at your option) any later version.
11 *
12 * HeuristicLab is distributed in the hope that it will be useful,
13 * but WITHOUT ANY WARRANTY; without even the implied warranty of
14 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
15 * GNU General Public License for more details.
16 *
17 * You should have received a copy of the GNU General Public License
18 * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
19 */
20#endregion
21
22using System;
23using System.Collections.Generic;
24using System.Linq;
25using HeuristicLab.Random;
26
27namespace HeuristicLab.Problems.Instances.DataAnalysis {
28  class AircraftLift : ArtificialRegressionDataDescriptor {
29    public override string Name { get { return "Aircraft Lift Coefficient C_L = x1*(x2 - 2) + x3*x4*x5/x6"; } }
30
31    public override string Description {
32      get {
33        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 +
34               "Authors: Chen Chen, Changtong Luo, Zonglin Jiang" + Environment.NewLine +
35               "Function: f(X) = x1*(x2 - 2) + x3*x4*x5/x6" + Environment.NewLine +
36               "with x1 in [0.4, 0.8], x2 in [5, 10], x3 in [0.4, 0.8], x4 in [5, 10], x5 in [1, 1.5], x6 in [5, 7]";
37      }
38    }
39
40    protected override string TargetVariable { get { return "f(X)"; } }
41    protected override string[] VariableNames { get { return new string[] { "x1", "x2", "x3", "x4", "x5", "x6", "f(X)" }; } }
42    protected override string[] AllowedInputVariables { get { return new string[] { "x1", "x2", "x3", "x4", "x5", "x6" }; } }
43    protected override int TrainingPartitionStart { get { return 0; } }
44    protected override int TrainingPartitionEnd { get { return 100; } }
45    protected override int TestPartitionStart { get { return 100; } }
46    protected override int TestPartitionEnd { get { return 200; } }
47
48    public int Seed { get; private set; }
49
50    public AircraftLift() : this((int)System.DateTime.Now.Ticks) { }
51
52    public AircraftLift(int seed) {
53      Seed = seed;
54    }
55
56    protected override List<List<double>> GenerateValues() {
57      var rand = new MersenneTwister((uint)Seed);
58
59      List<List<double>> data = new List<List<double>>();
60      var x1 = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 0.4, 0.8).ToList();
61      var x2 = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 5.0, 10.0).ToList();
62      var x3 = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 0.4, 0.8).ToList();
63      var x4 = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 5.0, 10.0).ToList();
64      var x5 = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 1.0, 1.5).ToList();
65      var x6 = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 5.0, 7.0).ToList();
66
67      List<double> fx = new List<double>();
68      data.Add(x1);
69      data.Add(x2);
70      data.Add(x3);
71      data.Add(x4);
72      data.Add(x5);
73      data.Add(x6);
74      data.Add(fx);
75
76      for (int i = 0; i < x1.Count; i++) {
77        double fxi = x1[i] * (x2[i] - 2.0) + x3[i] * x4[i] * x5[i] / x6[i];
78        fx.Add(fxi);
79      }
80
81      return data;
82    }
83  }
84}
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