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Neural Networks on C#

, 19 Nov 2006 GPL3
The articles describes a C# library for neural network computations, and their application for several problem solving.
neuro_demo.zip
neuro_demo
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
neuro_src.zip
neuro_src
Docs
AForge.Core.chm
AForge.Neuro.chm
Release
AForge.Controls.dll
AForge.dll
AForge.Neuro.dll
Samples
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
Core
Neuro
Activation Functions
Images
sigmoid.bmp
sigmoid_bipolar.bmp
threshold.bmp
Layers
Learning
Networks
Neurons
// AForge Framework
// Traveling Salesman Problem using Elastic Net
//
// 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 AForge;
using AForge.Neuro;
using AForge.Neuro.Learning;
using AForge.Controls;

namespace TSP
{
	/// <summary>
	/// Summary description for Form1.
	/// </summary>
	public class MainForm : System.Windows.Forms.Form
	{
		private System.Windows.Forms.GroupBox groupBox1;
		private System.Windows.Forms.Button generateMapButton;
		private System.Windows.Forms.TextBox citiesCountBox;
		private System.Windows.Forms.Label label1;
		private System.Windows.Forms.GroupBox groupBox2;
		private System.Windows.Forms.Label label2;
		private System.Windows.Forms.TextBox neuronsBox;
		private System.Windows.Forms.Label label3;
		private System.Windows.Forms.TextBox currentIterationBox;
		private System.Windows.Forms.Label label8;
		private System.Windows.Forms.Label label7;
		private System.Windows.Forms.TextBox rateBox;
		private System.Windows.Forms.Label label5;
		private System.Windows.Forms.TextBox iterationsBox;
		private System.Windows.Forms.Label label6;
		private System.Windows.Forms.Button stopButton;
		private System.Windows.Forms.Button startButton;
		private AForge.Controls.Chart chart;
		private System.Windows.Forms.Label label4;
		private System.Windows.Forms.TextBox radiusBox;
		/// <summary>
		/// Required designer variable.
		/// </summary>
		private System.ComponentModel.Container components = null;

		private int citiesCount		= 10;
		private int neurons			= 20;
		private int	iterations		= 500;
		private double learningRate	= 0.5;
		private double learningRadius = 0.5;

		private double[,]	map = null;
		private Random		rand = new Random();

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

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

			// initialize chart
			chart.AddDataSeries( "cities", Color.Red, Chart.SeriesType.Dots, 5, false );
			chart.AddDataSeries( "path", Color.Blue, Chart.SeriesType.Line, 1, false );
			chart.RangeX = new DoubleRange( 0, 1000 );
			chart.RangeY = new DoubleRange( 0, 1000 );

			//
			UpdateSettings( );
			GenerateMap( );
		}

		/// <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.generateMapButton = new System.Windows.Forms.Button();
			this.citiesCountBox = new System.Windows.Forms.TextBox();
			this.label1 = new System.Windows.Forms.Label();
			this.groupBox2 = new System.Windows.Forms.GroupBox();
			this.stopButton = new System.Windows.Forms.Button();
			this.startButton = new System.Windows.Forms.Button();
			this.currentIterationBox = new System.Windows.Forms.TextBox();
			this.label8 = new System.Windows.Forms.Label();
			this.label7 = new System.Windows.Forms.Label();
			this.rateBox = new System.Windows.Forms.TextBox();
			this.label5 = new System.Windows.Forms.Label();
			this.iterationsBox = new System.Windows.Forms.TextBox();
			this.label6 = new System.Windows.Forms.Label();
			this.label3 = new System.Windows.Forms.Label();
			this.neuronsBox = new System.Windows.Forms.TextBox();
			this.label2 = new System.Windows.Forms.Label();
			this.label4 = new System.Windows.Forms.Label();
			this.radiusBox = new System.Windows.Forms.TextBox();
			this.groupBox1.SuspendLayout();
			this.groupBox2.SuspendLayout();
			this.SuspendLayout();
			this.chart = new AForge.Controls.Chart( );
			// 
			// groupBox1
			// 
			this.groupBox1.Controls.Add(this.generateMapButton);
			this.groupBox1.Controls.Add(this.citiesCountBox);
			this.groupBox1.Controls.Add(this.label1);
			this.groupBox1.Controls.Add(this.chart);
			this.groupBox1.Location = new System.Drawing.Point(10, 10);
			this.groupBox1.Name = "groupBox1";
			this.groupBox1.Size = new System.Drawing.Size(300, 340);
			this.groupBox1.TabIndex = 1;
			this.groupBox1.TabStop = false;
			this.groupBox1.Text = "Map";
			// 
			// generateMapButton
			// 
			this.generateMapButton.Location = new System.Drawing.Point(110, 309);
			this.generateMapButton.Name = "generateMapButton";
			this.generateMapButton.Size = new System.Drawing.Size(75, 22);
			this.generateMapButton.TabIndex = 3;
			this.generateMapButton.Text = "&Generate";
			this.generateMapButton.Click += new System.EventHandler(this.generateMapButton_Click);
			// 
			// citiesCountBox
			// 
			this.citiesCountBox.Location = new System.Drawing.Point(50, 310);
			this.citiesCountBox.Name = "citiesCountBox";
			this.citiesCountBox.Size = new System.Drawing.Size(50, 20);
			this.citiesCountBox.TabIndex = 2;
			this.citiesCountBox.Text = "";
			// 
			// label1
			// 
			this.label1.Location = new System.Drawing.Point(10, 312);
			this.label1.Name = "label1";
			this.label1.Size = new System.Drawing.Size(40, 16);
			this.label1.TabIndex = 1;
			this.label1.Text = "Cities:";
			// 
			// chart
			// 
			this.chart.Location = new System.Drawing.Point(10, 20);
			this.chart.Name = "chart";
			this.chart.Size = new System.Drawing.Size(280, 280);
			this.chart.TabIndex = 4;
			// 
			// groupBox2
			// 
			this.groupBox2.Controls.Add(this.radiusBox);
			this.groupBox2.Controls.Add(this.label4);
			this.groupBox2.Controls.Add(this.stopButton);
			this.groupBox2.Controls.Add(this.startButton);
			this.groupBox2.Controls.Add(this.currentIterationBox);
			this.groupBox2.Controls.Add(this.label8);
			this.groupBox2.Controls.Add(this.label7);
			this.groupBox2.Controls.Add(this.rateBox);
			this.groupBox2.Controls.Add(this.label5);
			this.groupBox2.Controls.Add(this.iterationsBox);
			this.groupBox2.Controls.Add(this.label6);
			this.groupBox2.Controls.Add(this.label3);
			this.groupBox2.Controls.Add(this.neuronsBox);
			this.groupBox2.Controls.Add(this.label2);
			this.groupBox2.Location = new System.Drawing.Point(320, 10);
			this.groupBox2.Name = "groupBox2";
			this.groupBox2.Size = new System.Drawing.Size(180, 340);
			this.groupBox2.TabIndex = 2;
			this.groupBox2.TabStop = false;
			this.groupBox2.Text = "Neural Network";
			// 
			// stopButton
			// 
			this.stopButton.Enabled = false;
			this.stopButton.Location = new System.Drawing.Point(95, 305);
			this.stopButton.Name = "stopButton";
			this.stopButton.TabIndex = 23;
			this.stopButton.Text = "S&top";
			this.stopButton.Click += new System.EventHandler(this.stopButton_Click);
			// 
			// startButton
			// 
			this.startButton.Location = new System.Drawing.Point(10, 305);
			this.startButton.Name = "startButton";
			this.startButton.TabIndex = 22;
			this.startButton.Text = "&Start";
			this.startButton.Click += new System.EventHandler(this.startButton_Click);
			// 
			// currentIterationBox
			// 
			this.currentIterationBox.Location = new System.Drawing.Point(110, 150);
			this.currentIterationBox.Name = "currentIterationBox";
			this.currentIterationBox.ReadOnly = true;
			this.currentIterationBox.Size = new System.Drawing.Size(60, 20);
			this.currentIterationBox.TabIndex = 21;
			this.currentIterationBox.Text = "";
			// 
			// label8
			// 
			this.label8.Location = new System.Drawing.Point(10, 152);
			this.label8.Name = "label8";
			this.label8.Size = new System.Drawing.Size(100, 16);
			this.label8.TabIndex = 20;
			this.label8.Text = "Curren iteration:";
			// 
			// label7
			// 
			this.label7.BorderStyle = System.Windows.Forms.BorderStyle.FixedSingle;
			this.label7.Location = new System.Drawing.Point(10, 139);
			this.label7.Name = "label7";
			this.label7.Size = new System.Drawing.Size(160, 2);
			this.label7.TabIndex = 19;
			// 
			// rateBox
			// 
			this.rateBox.Location = new System.Drawing.Point(110, 85);
			this.rateBox.Name = "rateBox";
			this.rateBox.Size = new System.Drawing.Size(60, 20);
			this.rateBox.TabIndex = 18;
			this.rateBox.Text = "";
			// 
			// label5
			// 
			this.label5.Location = new System.Drawing.Point(10, 87);
			this.label5.Name = "label5";
			this.label5.Size = new System.Drawing.Size(100, 16);
			this.label5.TabIndex = 17;
			this.label5.Text = "Initial learning rate:";
			// 
			// iterationsBox
			// 
			this.iterationsBox.Location = new System.Drawing.Point(110, 60);
			this.iterationsBox.Name = "iterationsBox";
			this.iterationsBox.Size = new System.Drawing.Size(60, 20);
			this.iterationsBox.TabIndex = 16;
			this.iterationsBox.Text = "";
			// 
			// label6
			// 
			this.label6.Location = new System.Drawing.Point(10, 62);
			this.label6.Name = "label6";
			this.label6.Size = new System.Drawing.Size(60, 16);
			this.label6.TabIndex = 15;
			this.label6.Text = "Iteraions:";
			// 
			// label3
			// 
			this.label3.BorderStyle = System.Windows.Forms.BorderStyle.FixedSingle;
			this.label3.Location = new System.Drawing.Point(10, 48);
			this.label3.Name = "label3";
			this.label3.Size = new System.Drawing.Size(160, 2);
			this.label3.TabIndex = 4;
			// 
			// neuronsBox
			// 
			this.neuronsBox.Location = new System.Drawing.Point(110, 20);
			this.neuronsBox.Name = "neuronsBox";
			this.neuronsBox.Size = new System.Drawing.Size(60, 20);
			this.neuronsBox.TabIndex = 1;
			this.neuronsBox.Text = "";
			// 
			// label2
			// 
			this.label2.Location = new System.Drawing.Point(10, 22);
			this.label2.Name = "label2";
			this.label2.Size = new System.Drawing.Size(60, 16);
			this.label2.TabIndex = 0;
			this.label2.Text = "Neurons:";
			// 
			// label4
			// 
			this.label4.Location = new System.Drawing.Point(10, 112);
			this.label4.Name = "label4";
			this.label4.Size = new System.Drawing.Size(100, 16);
			this.label4.TabIndex = 24;
			this.label4.Text = "Learning radius:";
			// 
			// radiusBox
			// 
			this.radiusBox.Location = new System.Drawing.Point(110, 110);
			this.radiusBox.Name = "radiusBox";
			this.radiusBox.Size = new System.Drawing.Size(60, 20);
			this.radiusBox.TabIndex = 25;
			this.radiusBox.Text = "";
			// 
			// MainForm
			// 
			this.AutoScaleBaseSize = new System.Drawing.Size(5, 13);
			this.ClientSize = new System.Drawing.Size(509, 360);
			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 = "Traveling Salesman Problem using Elastic Net";
			this.Closing += new System.ComponentModel.CancelEventHandler(this.MainForm_Closing);
			this.groupBox1.ResumeLayout(false);
			this.groupBox2.ResumeLayout(false);
			this.ResumeLayout(false);

		}
		#endregion

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

		// 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;
				workerThread.Join( );
			}
		}

		// Update settings controls
		private void UpdateSettings( )
		{
			citiesCountBox.Text	= citiesCount.ToString( );
			neuronsBox.Text		= neurons.ToString( );
			iterationsBox.Text	= iterations.ToString( );
			rateBox.Text		= learningRate.ToString( );
			radiusBox.Text		= learningRadius.ToString( );
		}

		// Generate new map for the Traivaling Salesman problem
		private void GenerateMap( )
		{
			Random rand = new Random( (int) DateTime.Now.Ticks );

			// create coordinates array
			map = new double[citiesCount, 2];

			for ( int i = 0; i < citiesCount; i++ )
			{
				map[i, 0] = rand.Next( 1001 );
				map[i, 1] = rand.Next( 1001 );
			}

			// set the map
			chart.UpdateDataSeries( "cities", map );
			// erase path if it is
			chart.UpdateDataSeries( "path", null );
		}

		// On "Generate" button click - generate map
		private void generateMapButton_Click(object sender, System.EventArgs e)
		{
			// get cities count
			try
			{
				citiesCount = Math.Max( 5, Math.Min( 50, int.Parse( citiesCountBox.Text ) ) );
			}
			catch
			{
				citiesCount = 20;
			}
			citiesCountBox.Text = citiesCount.ToString( );

			// regenerate map
			GenerateMap( );
		}

		// Enable/disale controls
		private void EnableControls( bool enable )
		{
			neuronsBox.Enabled		= enable;
			iterationsBox.Enabled	= enable;
			rateBox.Enabled			= enable;
			radiusBox.Enabled		= enable;

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

		// On "Start" button click
		private void startButton_Click(object sender, System.EventArgs e)
		{
			// get network size
			try
			{
				neurons = Math.Max( 5, Math.Min( 50, int.Parse( neuronsBox.Text ) ) );
			}
			catch
			{
				neurons = 20;
			}
			// get iterations count
			try
			{
				iterations = Math.Max( 10, Math.Min( 1000000, int.Parse( iterationsBox.Text ) ) );
			}
			catch
			{
				iterations = 500;
			}
			// get learning rate
			try
			{
				learningRate = Math.Max( 0.00001, Math.Min( 1.0, double.Parse( rateBox.Text ) ) );
			}
			catch
			{
				learningRate = 0.5;
			}
			// get learning radius
			try
			{
				learningRadius = Math.Max( 0.00001, Math.Min( 1.0, double.Parse( radiusBox.Text ) ) );
			}
			catch
			{
				learningRadius = 0.5;
			}
			// 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 "Stop" button click
		private void stopButton_Click(object sender, System.EventArgs e)
		{
			// stop worker thread
			needToStop = true;
			workerThread.Join( );
			workerThread = null;
		}

		// Worker thread
		void SearchSolution( )
		{
			// set random generators range
			Neuron.RandRange = new DoubleRange( 0, 1000 );

			// create network
			DistanceNetwork network = new DistanceNetwork( 2, neurons );

			// create learning algorithm
			ElasticNetworkLearning	trainer = new ElasticNetworkLearning( network );

			double	fixedLearningRate = learningRate / 20;
			double	driftingLearningRate = fixedLearningRate * 19;

			// path
			double[,] path = new double[neurons + 1, 2];

			// input
			double[] input = new double[2];

			// iterations
			int i = 0;

			// loop
			while ( !needToStop )
			{
				// update learning speed & radius
				trainer.LearningRate = driftingLearningRate * ( iterations - i ) / iterations + fixedLearningRate;
				trainer.LearningRadius = learningRadius * ( iterations - i ) / iterations;

				// set network input
				int currentCity = rand.Next( citiesCount );
				input[0] = map[currentCity, 0];
				input[1] = map[currentCity, 1];

				// run one training iteration
				trainer.Run( input );

				// show current path
				for ( int j = 0; j < neurons; j++ )
				{
					path[j, 0] = network[0][j][0];
					path[j, 1] = network[0][j][1];
				}
				path[neurons, 0] = network[0][0][0];
				path[neurons, 1] = network[0][0][1];

				chart.UpdateDataSeries( "path", path );

				// increase current iteration
				i++;

				// set current iteration's info
				currentIterationBox.Text = i.ToString( );

				// stop ?
				if ( i >= iterations )
					break;
			}

			// 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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Web01 | 2.8.141223.1 | Last Updated 19 Nov 2006
Article Copyright 2006 by Andrew Kirillov
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