#region License Information /* HeuristicLab * Copyright (C) 2002-2019 Heuristic and Evolutionary Algorithms Laboratory (HEAL) * * This file is part of HeuristicLab. * * HeuristicLab is free software: you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * HeuristicLab is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with HeuristicLab. If not, see . */ #endregion using System; using System.Collections.Generic; using System.Linq; using HeuristicLab.Random; namespace HeuristicLab.Problems.Instances.DataAnalysis { public class RocketFuelFlow : ArtificialRegressionDataDescriptor { public override string Name { get { return "Rocket Fuel Flow m_dot = p0 A / sqrt(T0) * sqrt(γ/R (2/(γ+1))^((γ+1) / (γ-1)))"; } } public override string Description { get { 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: m_dot = p0 A / sqrt(T0) * sqrt(γ/R (2/(γ+1))^((γ+1) / (γ-1)))" + Environment.NewLine + "with p0 ∈ [4e5 Pa, 6e5 Pa]," + Environment.NewLine + "A ∈ [0.5m², 1.5m²]," + Environment.NewLine + "T0 ∈ [250°K, 260°K]," + Environment.NewLine + "γ=1.4 and R=287 J/(kg*K)" + Environment.NewLine + "The factor sqrt(γ/R (2/(γ+1))^((γ+1) / (γ-1))) is constant as γ and R are constants."; } } protected override string TargetVariable { get { return "m_dot"; } } protected override string[] VariableNames { get { return new string[] { "p0", "A", "T0", "m_dot" }; } } protected override string[] AllowedInputVariables { get { return new string[] { "p0", "A", "T0" }; } } protected override int TrainingPartitionStart { get { return 0; } } protected override int TrainingPartitionEnd { get { return 100; } } protected override int TestPartitionStart { get { return 100; } } protected override int TestPartitionEnd { get { return 200; } } public int Seed { get; private set; } public RocketFuelFlow() : this((int)System.DateTime.Now.Ticks) { } public RocketFuelFlow(int seed) { Seed = seed; } protected override List> GenerateValues() { var rand = new MersenneTwister((uint)Seed); List> data = new List>(); var p0 = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 4.0e5, 6.0e5).ToList(); var A = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 0.5, 1.5).ToList(); var T0 = ValueGenerator.GenerateUniformDistributedValues(rand.Next(), TestPartitionEnd, 250.0, 260.0).ToList(); List m_dot = new List(); data.Add(p0); data.Add(A); data.Add(T0); data.Add(m_dot); double R = 287.0; double γ = 1.4; var c = Math.Sqrt(γ / R * Math.Pow(2 / (γ + 1), (γ + 1) / (γ - 1))); for (int i = 0; i < p0.Count; i++) { double m_dot_i = p0[i] * A[i] / Math.Sqrt(T0[i]) * c; m_dot.Add(m_dot_i); } return data; } } }