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AForge.NET open source framework

, 16 May 2007 GPL3
The article describes an open source C# framework for researchers in the areas of Computer Vision and Artificial Intelligence - image processing, neural networks, genetic algorithms, etc.
aforge_demo.zip
aforge_demo
Docs
AForge.Controls.chm
AForge.Core.chm
AForge.Genetic.chm
AForge.Imaging.chm
AForge.Math.chm
AForge.Neuro.chm
Release
AForge.Controls.dll
AForge.dll
AForge.Genetic.dll
AForge.Imaging.dll
AForge.Math.dll
AForge.Neuro.dll
Samples
Genetic
Approximation
AForge.Controls.dll
AForge.dll
AForge.Genetic.dll
Approximation.exe
Data Samples
sample1.csv
sample2.csv
Optimization1D
AForge.Controls.dll
AForge.dll
AForge.Genetic.dll
Optimization1D.exe
TimeSeries
AForge.Controls.dll
AForge.dll
AForge.Genetic.dll
Data Samples
exponent.csv
growing sinusoid.csv
parabola.csv
sigmoid.csv
sinusoid.csv
TimeSeries.exe
TSP
AForge.Controls.dll
AForge.dll
AForge.Genetic.dll
TSP.exe
Imaging
FiltersDemo
AForge.dll
AForge.Imaging.dll
AForge.Math.dll
FiltersDemo.exe
TexturesDemo
AForge.dll
AForge.Imaging.dll
AForge.Math.dll
TexturesDemo.exe
Neuro
Back Propagation
Approximation
AForge.Controls.dll
AForge.dll
AForge.Neuro.dll
Approximation.exe
Data Samples
sample1.csv
sample2.csv
TimeSeries
AForge.Controls.dll
AForge.dll
AForge.Neuro.dll
Data Samples
exponent.csv
growing sinusoid.csv
parabola.csv
sigmoid.csv
sinusoid.csv
TimeSeries.exe
XORProblem
AForge.Controls.dll
AForge.dll
AForge.Neuro.dll
XORProblem.exe
Simple
Delta Rule Learning
AForge.Controls.dll
AForge.dll
AForge.Neuro.dll
Classifier.exe
Data Samples
and.csv
cube.csv
or.csv
sample1.csv
sample2.csv
One-Layer Perceptron Classifier
AForge.Controls.dll
AForge.dll
AForge.Neuro.dll
Classifier.exe
Data Samples
sample1.csv
sample2.csv
Perceptron Classifier
AForge.Controls.dll
AForge.dll
AForge.Neuro.dll
Classifier.exe
Data Samples
and.csv
cube.csv
or.csv
SOM
2DOrganizing
2DOrganizing.exe
AForge.dll
AForge.Neuro.dll
Color
AForge.dll
AForge.Neuro.dll
Color.exe
TSP
AForge.Controls.dll
AForge.dll
AForge.Neuro.dll
TSP.exe
aforge_src.zip
aforge_src
Samples
Genetic
Approximation
App.ico
Data Samples
sample1.csv
sample2.csv
Optimization1D
App.ico
TimeSeries
App.ico
Data Samples
exponent.csv
growing sinusoid.csv
parabola.csv
sigmoid.csv
sinusoid.csv
TSP
App.ico
Imaging
FiltersDemo
App.ico
TexturesDemo
Properties
Neuro
Back Propagation
Approximation
App.ico
Data Samples
sample1.csv
sample2.csv
TimeSeries
App.ico
Data Samples
exponent.csv
growing sinusoid.csv
parabola.csv
sigmoid.csv
sinusoid.csv
XORProblem
App.ico
Simple
Delta Rule Learning
App.ico
Data Samples
and.csv
cube.csv
or.csv
sample1.csv
sample2.csv
One-Layer Perceptron Classifier
App.ico
Data Samples
sample1.csv
sample2.csv
Perceptron Classifier
App.ico
Data Samples
and.csv
cube.csv
or.csv
SOM
2DOrganizing
App.ico
Color
App.ico
TSP
App.ico
Sources
Controls
bin
Debug
obj
Debug
TempPE
Core
bin
Debug
obj
Debug
TempPE
Docs Projects
AForge.Controls.shfb
AForge.Core.shfb
AForge.Genetic.shfb
AForge.Imaging.shfb
AForge.Math.shfb
AForge.Neuro.shfb
Genetic
bin
Debug
Chromosomes
GP
Fitness Functions
obj
Debug
TempPE
Selection Algorithms
Imaging
bin
Debug
Filters
2 Source filters
Adaptive Binarization
Base classes
Binarization
Color Filters
Convolution
Edge Detectors
HSL Filters
Morphology
Other
Transform
YCbCr Filters
Images
sample1.jpg
sepia.jpg
obj
Debug
TempPE
Textures
Math
bin
Debug
obj
Debug
TempPE
Neuro
Activation Functions
bin
Debug
Images
sigmoid.bmp
sigmoid_bipolar.bmp
threshold.bmp
Layers
Learning
Networks
Neurons
obj
Debug
TempPE
// AForge Framework
// Time Series Prediction using Multi-Layer Neural Network
//
// Copyright � Andrew Kirillov, 2006
// andrew.kirillov@gmail.com
//

using System;
using System.Drawing;
using System.Collections;
using System.ComponentModel;
using System.Windows.Forms;
using System.Data;
using System.Threading;
using System.IO;

using AForge;
using AForge.Neuro;
using AForge.Neuro.Learning;
using AForge.Controls;

namespace TimeSeries
{
	/// <summary>
	/// Summary description for Form1.
	/// </summary>
	public class MainForm : System.Windows.Forms.Form
	{
		private System.Windows.Forms.GroupBox groupBox1;
		private System.Windows.Forms.ListView dataList;
		private System.Windows.Forms.ColumnHeader yColumnHeader;
		private System.Windows.Forms.ColumnHeader estimatedYColumnHeader;
		private System.Windows.Forms.Button loadDataButton;
		private System.Windows.Forms.GroupBox groupBox2;
		private AForge.Controls.Chart chart;
		private System.Windows.Forms.OpenFileDialog openFileDialog;
		private System.Windows.Forms.GroupBox groupBox3;
		private System.Windows.Forms.TextBox momentumBox;
		private System.Windows.Forms.Label label6;
		private System.Windows.Forms.TextBox alphaBox;
		private System.Windows.Forms.Label label2;
		private System.Windows.Forms.TextBox learningRateBox;
		private System.Windows.Forms.Label label1;
		private System.Windows.Forms.Label label10;
		private System.Windows.Forms.TextBox iterationsBox;
		private System.Windows.Forms.Label label9;
		private System.Windows.Forms.Label label8;
		private System.Windows.Forms.TextBox predictionSizeBox;
		private System.Windows.Forms.Label label7;
		private System.Windows.Forms.TextBox windowSizeBox;
		private System.Windows.Forms.Label label3;
		private System.Windows.Forms.Label label5;
		private System.Windows.Forms.Button stopButton;
		private System.Windows.Forms.Button startButton;
		private System.Windows.Forms.GroupBox groupBox4;
		private System.Windows.Forms.TextBox currentPredictionErrorBox;
		private System.Windows.Forms.Label label13;
		private System.Windows.Forms.TextBox currentLearningErrorBox;
		private System.Windows.Forms.Label label12;
		private System.Windows.Forms.TextBox currentIterationBox;
		private System.Windows.Forms.Label label11;
		/// <summary>
		/// Required designer variable.
		/// </summary>
		private System.ComponentModel.Container components = null;

		private double[]	data = null;
		private double[,]	dataToShow = null;

		private double		learningRate = 0.1;
		private double		momentum = 0.0;
		private double		sigmoidAlphaValue = 2.0;
		private int			windowSize = 5;
		private int			predictionSize = 1;
		private int			iterations = 1000;

		private Thread		workerThread = null;
		private bool		needToStop = false;

		private double[,]	windowDelimiter = new double[2, 2] { { 0, 0 }, { 0, 0 } };
		private double[,]	predictionDelimiter = new double[2, 2] { { 0, 0 }, { 0, 0 } };

		// Constructor
		public MainForm( )
		{
			//
			// Required for Windows Form Designer support
			//
			InitializeComponent();

			// initializa chart control
			chart.AddDataSeries( "data", Color.Red, Chart.SeriesType.Dots, 5 );
			chart.AddDataSeries( "solution", Color.Blue, Chart.SeriesType.Line, 1 );
			chart.AddDataSeries( "window", Color.LightGray, Chart.SeriesType.Line, 1, false );
			chart.AddDataSeries( "prediction", Color.Gray, Chart.SeriesType.Line, 1, false );

			// update controls
			UpdateSettings( );
		}

		/// <summary>
		/// Clean up any resources being used.
		/// </summary>
		protected override void Dispose( bool disposing )
		{
			if( disposing )
			{
				if (components != null) 
				{
					components.Dispose();
				}
			}
			base.Dispose( disposing );
		}

		#region Windows Form Designer generated code
		/// <summary>
		/// Required method for Designer support - do not modify
		/// the contents of this method with the code editor.
		/// </summary>
		private void InitializeComponent()
		{
			this.groupBox1 = new System.Windows.Forms.GroupBox();
			this.dataList = new System.Windows.Forms.ListView();
			this.yColumnHeader = new System.Windows.Forms.ColumnHeader();
			this.estimatedYColumnHeader = new System.Windows.Forms.ColumnHeader();
			this.loadDataButton = new System.Windows.Forms.Button();
			this.groupBox2 = new System.Windows.Forms.GroupBox();
			this.chart = new AForge.Controls.Chart();
			this.openFileDialog = new System.Windows.Forms.OpenFileDialog();
			this.groupBox3 = new System.Windows.Forms.GroupBox();
			this.momentumBox = new System.Windows.Forms.TextBox();
			this.label6 = new System.Windows.Forms.Label();
			this.alphaBox = new System.Windows.Forms.TextBox();
			this.label2 = new System.Windows.Forms.Label();
			this.learningRateBox = new System.Windows.Forms.TextBox();
			this.label1 = new System.Windows.Forms.Label();
			this.label8 = new System.Windows.Forms.Label();
			this.iterationsBox = new System.Windows.Forms.TextBox();
			this.predictionSizeBox = new System.Windows.Forms.TextBox();
			this.label7 = new System.Windows.Forms.Label();
			this.windowSizeBox = new System.Windows.Forms.TextBox();
			this.label3 = new System.Windows.Forms.Label();
			this.label10 = new System.Windows.Forms.Label();
			this.label9 = new System.Windows.Forms.Label();
			this.label5 = new System.Windows.Forms.Label();
			this.stopButton = new System.Windows.Forms.Button();
			this.startButton = new System.Windows.Forms.Button();
			this.groupBox4 = new System.Windows.Forms.GroupBox();
			this.currentPredictionErrorBox = new System.Windows.Forms.TextBox();
			this.label13 = new System.Windows.Forms.Label();
			this.currentLearningErrorBox = new System.Windows.Forms.TextBox();
			this.label12 = new System.Windows.Forms.Label();
			this.currentIterationBox = new System.Windows.Forms.TextBox();
			this.label11 = new System.Windows.Forms.Label();
			this.groupBox1.SuspendLayout();
			this.groupBox2.SuspendLayout();
			this.groupBox3.SuspendLayout();
			this.groupBox4.SuspendLayout();
			this.SuspendLayout();
			// 
			// groupBox1
			// 
			this.groupBox1.Controls.Add(this.dataList);
			this.groupBox1.Controls.Add(this.loadDataButton);
			this.groupBox1.Location = new System.Drawing.Point(10, 10);
			this.groupBox1.Name = "groupBox1";
			this.groupBox1.Size = new System.Drawing.Size(180, 380);
			this.groupBox1.TabIndex = 0;
			this.groupBox1.TabStop = false;
			this.groupBox1.Text = "Data";
			// 
			// dataList
			// 
			this.dataList.Columns.AddRange(new System.Windows.Forms.ColumnHeader[] {
																					   this.yColumnHeader,
																					   this.estimatedYColumnHeader});
			this.dataList.FullRowSelect = true;
			this.dataList.GridLines = true;
			this.dataList.Location = new System.Drawing.Point(10, 20);
			this.dataList.Name = "dataList";
			this.dataList.Size = new System.Drawing.Size(160, 315);
			this.dataList.TabIndex = 3;
			this.dataList.View = System.Windows.Forms.View.Details;
			// 
			// yColumnHeader
			// 
			this.yColumnHeader.Text = "Y:Real";
			this.yColumnHeader.Width = 70;
			// 
			// estimatedYColumnHeader
			// 
			this.estimatedYColumnHeader.Text = "Y:Estimated";
			this.estimatedYColumnHeader.Width = 70;
			// 
			// loadDataButton
			// 
			this.loadDataButton.Location = new System.Drawing.Point(10, 345);
			this.loadDataButton.Name = "loadDataButton";
			this.loadDataButton.TabIndex = 2;
			this.loadDataButton.Text = "&Load";
			this.loadDataButton.Click += new System.EventHandler(this.loadDataButton_Click);
			// 
			// groupBox2
			// 
			this.groupBox2.Controls.Add(this.chart);
			this.groupBox2.Location = new System.Drawing.Point(200, 10);
			this.groupBox2.Name = "groupBox2";
			this.groupBox2.Size = new System.Drawing.Size(300, 380);
			this.groupBox2.TabIndex = 2;
			this.groupBox2.TabStop = false;
			this.groupBox2.Text = "Function";
			// 
			// chart
			// 
			this.chart.Location = new System.Drawing.Point(10, 20);
			this.chart.Name = "chart";
			this.chart.Size = new System.Drawing.Size(280, 350);
			this.chart.TabIndex = 0;
			// 
			// openFileDialog
			// 
			this.openFileDialog.Filter = "CSV (Comma delimited) (*.csv)|*.csv";
			this.openFileDialog.Title = "Select data file";
			// 
			// groupBox3
			// 
			this.groupBox3.Controls.Add(this.momentumBox);
			this.groupBox3.Controls.Add(this.label6);
			this.groupBox3.Controls.Add(this.alphaBox);
			this.groupBox3.Controls.Add(this.label2);
			this.groupBox3.Controls.Add(this.learningRateBox);
			this.groupBox3.Controls.Add(this.label1);
			this.groupBox3.Controls.Add(this.label8);
			this.groupBox3.Controls.Add(this.iterationsBox);
			this.groupBox3.Controls.Add(this.predictionSizeBox);
			this.groupBox3.Controls.Add(this.label7);
			this.groupBox3.Controls.Add(this.windowSizeBox);
			this.groupBox3.Controls.Add(this.label3);
			this.groupBox3.Controls.Add(this.label10);
			this.groupBox3.Controls.Add(this.label9);
			this.groupBox3.Controls.Add(this.label5);
			this.groupBox3.Location = new System.Drawing.Point(510, 10);
			this.groupBox3.Name = "groupBox3";
			this.groupBox3.Size = new System.Drawing.Size(195, 205);
			this.groupBox3.TabIndex = 3;
			this.groupBox3.TabStop = false;
			this.groupBox3.Text = "Settings";
			// 
			// momentumBox
			// 
			this.momentumBox.Location = new System.Drawing.Point(125, 45);
			this.momentumBox.Name = "momentumBox";
			this.momentumBox.Size = new System.Drawing.Size(60, 20);
			this.momentumBox.TabIndex = 9;
			this.momentumBox.Text = "";
			// 
			// label6
			// 
			this.label6.Location = new System.Drawing.Point(10, 47);
			this.label6.Name = "label6";
			this.label6.Size = new System.Drawing.Size(82, 17);
			this.label6.TabIndex = 8;
			this.label6.Text = "Momentum:";
			// 
			// alphaBox
			// 
			this.alphaBox.Location = new System.Drawing.Point(125, 70);
			this.alphaBox.Name = "alphaBox";
			this.alphaBox.Size = new System.Drawing.Size(60, 20);
			this.alphaBox.TabIndex = 11;
			this.alphaBox.Text = "";
			// 
			// label2
			// 
			this.label2.Location = new System.Drawing.Point(10, 72);
			this.label2.Name = "label2";
			this.label2.Size = new System.Drawing.Size(120, 15);
			this.label2.TabIndex = 10;
			this.label2.Text = "Sigmoid\'s alpha value:";
			// 
			// learningRateBox
			// 
			this.learningRateBox.Location = new System.Drawing.Point(125, 20);
			this.learningRateBox.Name = "learningRateBox";
			this.learningRateBox.Size = new System.Drawing.Size(60, 20);
			this.learningRateBox.TabIndex = 7;
			this.learningRateBox.Text = "";
			// 
			// label1
			// 
			this.label1.Location = new System.Drawing.Point(10, 22);
			this.label1.Name = "label1";
			this.label1.Size = new System.Drawing.Size(78, 14);
			this.label1.TabIndex = 6;
			this.label1.Text = "Learning rate:";
			// 
			// label8
			// 
			this.label8.BorderStyle = System.Windows.Forms.BorderStyle.Fixed3D;
			this.label8.Location = new System.Drawing.Point(10, 157);
			this.label8.Name = "label8";
			this.label8.Size = new System.Drawing.Size(175, 2);
			this.label8.TabIndex = 22;
			// 
			// iterationsBox
			// 
			this.iterationsBox.Location = new System.Drawing.Point(125, 165);
			this.iterationsBox.Name = "iterationsBox";
			this.iterationsBox.Size = new System.Drawing.Size(60, 20);
			this.iterationsBox.TabIndex = 24;
			this.iterationsBox.Text = "";
			// 
			// predictionSizeBox
			// 
			this.predictionSizeBox.Location = new System.Drawing.Point(125, 130);
			this.predictionSizeBox.Name = "predictionSizeBox";
			this.predictionSizeBox.Size = new System.Drawing.Size(60, 20);
			this.predictionSizeBox.TabIndex = 21;
			this.predictionSizeBox.Text = "";
			this.predictionSizeBox.TextChanged += new System.EventHandler(this.predictionSizeBox_TextChanged);
			// 
			// label7
			// 
			this.label7.Location = new System.Drawing.Point(10, 132);
			this.label7.Name = "label7";
			this.label7.Size = new System.Drawing.Size(90, 16);
			this.label7.TabIndex = 20;
			this.label7.Text = "Prediction size:";
			// 
			// windowSizeBox
			// 
			this.windowSizeBox.Location = new System.Drawing.Point(125, 105);
			this.windowSizeBox.Name = "windowSizeBox";
			this.windowSizeBox.Size = new System.Drawing.Size(60, 20);
			this.windowSizeBox.TabIndex = 19;
			this.windowSizeBox.Text = "";
			this.windowSizeBox.TextChanged += new System.EventHandler(this.windowSizeBox_TextChanged);
			// 
			// label3
			// 
			this.label3.Location = new System.Drawing.Point(10, 107);
			this.label3.Name = "label3";
			this.label3.Size = new System.Drawing.Size(80, 16);
			this.label3.TabIndex = 18;
			this.label3.Text = "Window size:";
			// 
			// label10
			// 
			this.label10.Font = new System.Drawing.Font("Microsoft Sans Serif", 6.75F, System.Drawing.FontStyle.Regular, System.Drawing.GraphicsUnit.Point, ((System.Byte)(0)));
			this.label10.Location = new System.Drawing.Point(126, 185);
			this.label10.Name = "label10";
			this.label10.Size = new System.Drawing.Size(58, 14);
			this.label10.TabIndex = 25;
			this.label10.Text = "( 0 - inifinity )";
			// 
			// label9
			// 
			this.label9.Location = new System.Drawing.Point(10, 167);
			this.label9.Name = "label9";
			this.label9.Size = new System.Drawing.Size(70, 16);
			this.label9.TabIndex = 23;
			this.label9.Text = "Iterations:";
			// 
			// label5
			// 
			this.label5.BorderStyle = System.Windows.Forms.BorderStyle.Fixed3D;
			this.label5.Location = new System.Drawing.Point(10, 97);
			this.label5.Name = "label5";
			this.label5.Size = new System.Drawing.Size(175, 2);
			this.label5.TabIndex = 17;
			// 
			// stopButton
			// 
			this.stopButton.Enabled = false;
			this.stopButton.Location = new System.Drawing.Point(630, 360);
			this.stopButton.Name = "stopButton";
			this.stopButton.TabIndex = 6;
			this.stopButton.Text = "S&top";
			this.stopButton.Click += new System.EventHandler(this.stopButton_Click);
			// 
			// startButton
			// 
			this.startButton.Enabled = false;
			this.startButton.Location = new System.Drawing.Point(540, 360);
			this.startButton.Name = "startButton";
			this.startButton.TabIndex = 5;
			this.startButton.Text = "&Start";
			this.startButton.Click += new System.EventHandler(this.startButton_Click);
			// 
			// groupBox4
			// 
			this.groupBox4.Controls.Add(this.currentPredictionErrorBox);
			this.groupBox4.Controls.Add(this.label13);
			this.groupBox4.Controls.Add(this.currentLearningErrorBox);
			this.groupBox4.Controls.Add(this.label12);
			this.groupBox4.Controls.Add(this.currentIterationBox);
			this.groupBox4.Controls.Add(this.label11);
			this.groupBox4.Location = new System.Drawing.Point(510, 225);
			this.groupBox4.Name = "groupBox4";
			this.groupBox4.Size = new System.Drawing.Size(195, 100);
			this.groupBox4.TabIndex = 7;
			this.groupBox4.TabStop = false;
			this.groupBox4.Text = "Current iteration:";
			// 
			// currentPredictionErrorBox
			// 
			this.currentPredictionErrorBox.Location = new System.Drawing.Point(125, 70);
			this.currentPredictionErrorBox.Name = "currentPredictionErrorBox";
			this.currentPredictionErrorBox.ReadOnly = true;
			this.currentPredictionErrorBox.Size = new System.Drawing.Size(60, 20);
			this.currentPredictionErrorBox.TabIndex = 5;
			this.currentPredictionErrorBox.Text = "";
			// 
			// label13
			// 
			this.label13.Location = new System.Drawing.Point(10, 72);
			this.label13.Name = "label13";
			this.label13.Size = new System.Drawing.Size(100, 16);
			this.label13.TabIndex = 4;
			this.label13.Text = "Prediction error:";
			// 
			// currentLearningErrorBox
			// 
			this.currentLearningErrorBox.Location = new System.Drawing.Point(125, 45);
			this.currentLearningErrorBox.Name = "currentLearningErrorBox";
			this.currentLearningErrorBox.ReadOnly = true;
			this.currentLearningErrorBox.Size = new System.Drawing.Size(60, 20);
			this.currentLearningErrorBox.TabIndex = 3;
			this.currentLearningErrorBox.Text = "";
			// 
			// label12
			// 
			this.label12.Location = new System.Drawing.Point(10, 47);
			this.label12.Name = "label12";
			this.label12.Size = new System.Drawing.Size(80, 16);
			this.label12.TabIndex = 2;
			this.label12.Text = "Learning error:";
			// 
			// currentIterationBox
			// 
			this.currentIterationBox.Location = new System.Drawing.Point(125, 20);
			this.currentIterationBox.Name = "currentIterationBox";
			this.currentIterationBox.ReadOnly = true;
			this.currentIterationBox.Size = new System.Drawing.Size(60, 20);
			this.currentIterationBox.TabIndex = 1;
			this.currentIterationBox.Text = "";
			// 
			// label11
			// 
			this.label11.Location = new System.Drawing.Point(10, 22);
			this.label11.Name = "label11";
			this.label11.Size = new System.Drawing.Size(70, 16);
			this.label11.TabIndex = 0;
			this.label11.Text = "Iteration:";
			// 
			// MainForm
			// 
			this.AutoScaleBaseSize = new System.Drawing.Size(5, 13);
			this.ClientSize = new System.Drawing.Size(715, 398);
			this.Controls.Add(this.groupBox4);
			this.Controls.Add(this.stopButton);
			this.Controls.Add(this.startButton);
			this.Controls.Add(this.groupBox3);
			this.Controls.Add(this.groupBox2);
			this.Controls.Add(this.groupBox1);
			this.FormBorderStyle = System.Windows.Forms.FormBorderStyle.FixedDialog;
			this.MaximizeBox = false;
			this.Name = "MainForm";
			this.Text = "Time Series Prediction using Multi-Layer Neural Network";
			this.Closing += new System.ComponentModel.CancelEventHandler(this.MainForm_Closing);
			this.groupBox1.ResumeLayout(false);
			this.groupBox2.ResumeLayout(false);
			this.groupBox3.ResumeLayout(false);
			this.groupBox4.ResumeLayout(false);
			this.ResumeLayout(false);

		}
		#endregion

		/// <summary>
		/// The main entry point for the application.
		/// </summary>
		[STAThread]
		static void Main( ) 
		{
			Application.Run( new MainForm( ) );
		}

        // Delegates to enable async calls for setting controls properties
        private delegate void SetTextCallback( System.Windows.Forms.Control control, string text );
        private delegate void AddSubItemCallback( System.Windows.Forms.ListView control, int item, string subitemText );

        // Thread safe updating of control's text property
        private void SetText( System.Windows.Forms.Control control, string text )
        {
            if ( control.InvokeRequired )
            {
                SetTextCallback d = new SetTextCallback( SetText );
                Invoke( d, new object[] { control, text } );
            }
            else
            {
                control.Text = text;
            }
        }

        // Thread safe adding of subitem to list control
        private void AddSubItem( System.Windows.Forms.ListView control, int item, string subitemText )
        {
            if ( control.InvokeRequired )
            {
                AddSubItemCallback d = new AddSubItemCallback( AddSubItem );
                Invoke( d, new object[] { control, item, subitemText } );
            }
            else
            {
                control.Items[item].SubItems.Add( subitemText );
            }
        }

		// On main form closing
		private void MainForm_Closing(object sender, System.ComponentModel.CancelEventArgs e)
		{
			// check if worker thread is running
			if ( ( workerThread != null ) && ( workerThread.IsAlive ) )
			{
				needToStop = true;
                while ( !workerThread.Join( 100 ) )
                    Application.DoEvents( );
            }
		}

		// Update settings controls
		private void UpdateSettings( )
		{
			learningRateBox.Text	= learningRate.ToString( );
			momentumBox.Text		= momentum.ToString( );
			alphaBox.Text			= sigmoidAlphaValue.ToString( );
			windowSizeBox.Text		= windowSize.ToString( );
			predictionSizeBox.Text	= predictionSize.ToString( );
			iterationsBox.Text		= iterations.ToString( );
		}

		// Load data
		private void loadDataButton_Click(object sender, System.EventArgs e)
		{
			// show file selection dialog
			if ( openFileDialog.ShowDialog( ) == DialogResult.OK )
			{
				StreamReader reader = null;
				// read maximum 50 points
				double[] tempData = new double[50];

				try
				{
					// open selected file
					reader = File.OpenText( openFileDialog.FileName );
					string	str = null;
					int		i = 0;

					// read the data
					while ( ( i < 50 ) && ( ( str = reader.ReadLine( ) ) != null ) )
					{
						// parse the value
						tempData[i] = double.Parse( str );

						i++;
					}

					// allocate and set data
					data = new double[i];
					dataToShow = new double[i, 2];
					Array.Copy( tempData, 0, data, 0, i );
					for ( int j = 0; j < i; j++ )
					{
						dataToShow[j, 0] = j;
						dataToShow[j, 1] = data[j];
					}
				}
				catch (Exception)
				{
					MessageBox.Show( "Failed reading the file", "Error", MessageBoxButtons.OK, MessageBoxIcon.Error );
					return;
				}
				finally
				{
					// close file
					if ( reader != null )
						reader.Close( );
				}

				// update list and chart
				UpdateDataListView( );
				chart.RangeX = new DoubleRange( 0, data.Length - 1 );
				chart.UpdateDataSeries( "data", dataToShow );
				chart.UpdateDataSeries( "solution", null );
				// set delimiters
				UpdateDelimiters( );
				// enable "Start" button
				startButton.Enabled = true;
			}
		}

		// Update delimiters on the chart
		private void UpdateDelimiters( )
		{
			// window delimiter
			windowDelimiter[0, 0] = windowDelimiter[1, 0] = windowSize;
			windowDelimiter[0, 1] = chart.RangeY.Min;
			windowDelimiter[1, 1] = chart.RangeY.Max;
			chart.UpdateDataSeries( "window", windowDelimiter );
			// prediction delimiter
			predictionDelimiter[0, 0] = predictionDelimiter[1, 0] = data.Length - 1 - predictionSize;
			predictionDelimiter[0, 1] = chart.RangeY.Min;
			predictionDelimiter[1, 1] = chart.RangeY.Max;
			chart.UpdateDataSeries( "prediction", predictionDelimiter );
		}

		// Update data in list view
		private void UpdateDataListView( )
		{
			// remove all current records
			dataList.Items.Clear( );
			// add new records
			for ( int i = 0, n = data.GetLength( 0 ); i < n; i++ )
			{
				dataList.Items.Add( data[i].ToString( ) );
			}
		}

        // Delegates to enable async calls for setting controls properties
        private delegate void EnableCallback( bool enable );

        // Enable/disable controls
		private void EnableControls( bool enable )
		{
            if ( InvokeRequired )
            {
                EnableCallback d = new EnableCallback( EnableControls );
                Invoke( d, new object[] { enable } );
            }
            else
            {
			    loadDataButton.Enabled		= enable;
			    learningRateBox.Enabled		= enable;
			    momentumBox.Enabled			= enable;
			    alphaBox.Enabled			= enable;
			    windowSizeBox.Enabled		= enable;
			    predictionSizeBox.Enabled	= enable;
			    iterationsBox.Enabled		= enable;

			    startButton.Enabled			= enable;
			    stopButton.Enabled			= !enable;
    		}
        }

		// On window size changed
		private void windowSizeBox_TextChanged(object sender, System.EventArgs e)
		{
			UpdateWindowSize( );
		}

		// On prediction changed
		private void predictionSizeBox_TextChanged(object sender, System.EventArgs e)
		{
			UpdatePredictionSize( );		
		}

		// Update window size
		private void UpdateWindowSize( )
		{
			if ( data != null )
			{
				// get new window size value
				try
				{
					windowSize = Math.Max( 1, Math.Min( 15, int.Parse( windowSizeBox.Text ) ) );
				}
				catch
				{
					windowSize = 5;
				}
				// check if we have too few data
				if ( windowSize >= data.Length )
					windowSize = 1;
				// update delimiters
				UpdateDelimiters( );
			}
		}

		// Update prediction size
		private void UpdatePredictionSize( )
		{
			if ( data != null )
			{
				// get new prediction size value
				try
				{
					predictionSize = Math.Max( 1, Math.Min( 10, int.Parse( predictionSizeBox.Text ) ) );
				}
				catch
				{
					predictionSize = 1;
				}
				// check if we have too few data
				if ( data.Length - predictionSize - 1 < windowSize )
					predictionSize = 1;
				// update delimiters
				UpdateDelimiters( );
			}
		}

		// On button "Start"
		private void startButton_Click( object sender, System.EventArgs e )
		{
			// clear previous solution
			for ( int j = 0, n = data.Length; j < n; j++ )
			{
				if ( dataList.Items[j].SubItems.Count > 1 )
					dataList.Items[j].SubItems.RemoveAt( 1 );
			}

			// get learning rate
			try
			{
				learningRate = Math.Max( 0.00001, Math.Min( 1, double.Parse( learningRateBox.Text ) ) );
			}
			catch
			{
				learningRate = 0.1;
			}
			// get momentum
			try
			{
				momentum = Math.Max( 0, Math.Min( 0.5, double.Parse( momentumBox.Text ) ) );
			}
			catch
			{
				momentum = 0;
			}
			// get sigmoid's alpha value
			try
			{
				sigmoidAlphaValue = Math.Max( 0.001, Math.Min( 50, double.Parse( alphaBox.Text ) ) );
			}
			catch
			{
				sigmoidAlphaValue = 2;
			}
			// iterations
			try
			{
				iterations = Math.Max( 0, int.Parse( iterationsBox.Text ) );
			}
			catch
			{
				iterations = 1000;
			}
			// update settings controls
			UpdateSettings( );
		
			// disable all settings controls except "Stop" button
			EnableControls( false );

			// run worker thread
			needToStop = false;
			workerThread = new Thread( new ThreadStart( SearchSolution ) );
			workerThread.Start( );
		}

		// On button "Stop"
		private void stopButton_Click( object sender, System.EventArgs e )
		{
			// stop worker thread
			needToStop = true;
            while ( !workerThread.Join( 100 ) )
                Application.DoEvents( );
            workerThread = null;
		}

		// Worker thread
		void SearchSolution( )
		{
			// number of learning samples
			int samples = data.Length - predictionSize - windowSize;
			// data transformation factor
			double factor = 1.7 / chart.RangeY.Length;
			double yMin = chart.RangeY.Min;
			// prepare learning data
			double[][] input = new double[samples][];
			double[][] output = new double[samples][];

			for ( int i = 0; i < samples; i++ )
			{
				input[i] = new double[windowSize];
				output[i] = new double[1];
			
				// set input
				for ( int j = 0; j < windowSize; j++ )
				{
					input[i][j] = ( data[i + j] - yMin ) * factor - 0.85;
				}
				// set output
				output[i][0] = ( data[i + windowSize] - yMin ) * factor - 0.85;
			}

			// create multi-layer neural network
			ActivationNetwork	network = new ActivationNetwork(
				new BipolarSigmoidFunction( sigmoidAlphaValue ),
				windowSize, windowSize * 2, 1 );
			// create teacher
			BackPropagationLearning teacher = new BackPropagationLearning( network );
			// set learning rate and momentum
			teacher.LearningRate	= learningRate;
			teacher.Momentum		= momentum;

			// iterations
			int iteration = 1;

			// solution array
			int			solutionSize = data.Length - windowSize;
			double[,]	solution = new double[solutionSize, 2];
			double[]	networkInput = new double[windowSize];

			// calculate X values to be used with solution function
			for ( int j = 0; j < solutionSize; j++ )
			{
				solution[j, 0] = j + windowSize;
			}
			
			// loop
			while ( !needToStop )
			{
				// run epoch of learning procedure
				double error = teacher.RunEpoch( input, output ) / samples;
			
				// calculate solution and learning and prediction errors
				double learningError = 0.0;
				double predictionError = 0.0;
				// go through all the data
				for ( int i = 0, n = data.Length - windowSize; i < n; i++ )
				{
					// put values from current window as network's input
					for ( int j = 0; j < windowSize; j++ )
					{
						networkInput[j] = ( data[i + j] - yMin ) * factor - 0.85;
					}

					// evalue the function
					solution[i, 1] = ( network.Compute( networkInput)[0] + 0.85 ) / factor + yMin;

					// calculate prediction error
					if ( i >= n - predictionSize )
					{
						predictionError += Math.Abs( solution[i, 1] - data[windowSize + i] );
					}
					else
					{
						learningError += Math.Abs( solution[i, 1] - data[windowSize + i] );
					}
				}
				// update solution on the chart
				chart.UpdateDataSeries( "solution", solution );

				// set current iteration's info
				SetText( currentIterationBox, iteration.ToString( ) );
				SetText( currentLearningErrorBox, learningError.ToString( "F3" ) );
				SetText( currentPredictionErrorBox, predictionError.ToString( "F3" ) );

				// increase current iteration
				iteration++;

				// check if we need to stop
				if ( ( iterations != 0 ) && ( iteration > iterations ) )
					break;
			}
			
			// show new solution
			for ( int j = windowSize, k = 0, n = data.Length; j < n; j++, k++ )
			{
                AddSubItem( dataList, j, solution[k, 1].ToString( ) );
            }

			// enable settings controls
			EnableControls( true );
		}
	}
}

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About the Author

Andrew Kirillov
Software Developer (Senior) Cisco Systems
United Kingdom United Kingdom
Started software development at about 15 years old and it seems like now it lasts most part of my life. Fortunately did not spend too much time with Z80 and BK0010 and switched to 8086 and further. Similar with programming languages – luckily managed to get away from BASIC and Pascal to things like Assembler, C, C++ and then C#. Apart from daily programming for food, do it also for hobby, where mostly enjoy areas like Computer Vision, Robotics and AI. This led to some open source stuff like AForge.NET.
 
Going out of computers I am just a man loving his family, enjoying traveling, a bit of books, a bit of movies and a mixture of everything else. Always wanted to learn playing guitar, but it seems like 6 strings are much harder than few dozens of keyboard’s keys. Will keep progressing ...

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