Mab.NeuralNetwork

In this library I want to write a basic library for neural network. I choose Visual Basic because of simplicity. But I'm going to port it to C++ in the feature. the first class that I implemented is Perceptron. In the next days I want to add other class for multi layer Neural Network and Genetic Algorithm for training it.

Perceptron

This class implemented Perceptron.

Sample Code:

Dim db As New List(Of PerceptronData)
Dim pr1 As New PerceptronData(0, 0, 0) ' add and oprator as a test data for our Perceptron
Dim pr2 As New PerceptronData(0, 0, 1)
Dim pr3 As New PerceptronData(0, 1, 0)
Dim pr4 As New PerceptronData(1, 1, 1)

db.Add(pr1)
db.Add(pr2)
db.Add(pr3)
db.Add(pr4)

Dim Machine As New Perceptron()
Machine.TrainByBackpropagation(db, 0.2) 'train our preseptron by our simple database :)

Genetic Algorithm

It is a class for solving problem by GA.

Sample Code: It solves NQeens Problem for a chess board by size of 16:

Dim gaSolver As New GA(16, 0, 16) With {
    .FitnessFunction = Function(ch)
                           Dim CurQueen As Integer
                           Dim TestQueen As Integer
                           Dim confilect As Integer
                           For i As Integer = 0 To ch.Genes.Length - 1
                               CurQueen = ch.Genes(i)
                               For j As Integer = 0 To ch.Genes.Length - 1
                                   TestQueen = ch.Genes(j)
                                   If (Not (i = j)) AndAlso ((TestQueen = CurQueen) OrElse (j - i) = (CurQueen - TestQueen) OrElse (i - j) = (CurQueen - TestQueen)) Then
                                       confilect += 1
                                   End If
                               Next
                           Next
                           Return confilect
                       End Function,
    .EndFunction = Function(ch, geneCount)
                       Return ch.Fitness = 0
                   End Function,
    .MutationRangeLength = 3,
    .MutationRate = 0.05,
    .PopulationCount = 100
}
gaSolver.MutationMethods.Add(New RandomResettingMutation())

gaSolver.CrossOverMethods.Add(New TwoPointCrossOver())
gaSolver.CrossOverMethods.Add(New UniformCrossOver())

AddHandler gaSolver.GenerationProduced, Sub()
                                            Console.CursorVisible = False
                                            Console.SetCursorPosition(0, 0)
                                            Console.Write(New String(" ", Console.WindowWidth))
                                            Console.SetCursorPosition(0, 0)
                                            Console.WriteLine($"Generation:{gaSolver.BestGenerations.Count} Fittnes:{gaSolver.BestGenerations.Last().Fitness}")
                                            Dim best = gaSolver.BestGenerations.Last()
                                            For i = 0 To gaSolver.MaxGeneValue - 1
                                                For j = 0 To gaSolver.MaxGeneValue - 1
                                                    If j = best.Genes(i) Then
                                                        Console.Write("1 ")
                                                    Else
                                                        Console.Write("0 ")
                                                    End If
                                                Next
                                                Console.WriteLine()
                                            Next
                                            Console.WriteLine()
                                        End Sub

gaSolver.Start()