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php - 如何将神经网络从 C 转换为 PHP

问题描述

我正在尝试将此算法从 C 语言翻译为 PHP（供研究） 这是感知器的一个示例。我复制了用 c 编写的示例，并尝试将其转换为 PHP。目前我写了这段代码，我错了什么？作为输出，我只知道 101 次迭代，结果总是 1。

这是C程序：

    #include <stdio.h>
#include <stdlib.h>
#include <math.h>
#include <time.h>

#define LEARNING_RATE    0.1
#define MAX_ITERATION    100

float randomFloat()
{
    return (float)rand() / (float)RAND_MAX;
}

int calculateOutput(float weights[], float x, float y)
{
    float sum = x * weights[0] + y * weights[1] + weights[2];
    return (sum >= 0) ? 1 : -1;
}

int main(int argc, char *argv[])
{
    srand(time(NULL));

    float x[208], y[208], weights[3], localError, globalError;
    int outputs[208], patternCount, i, p, iteration, output;

    FILE *fp;
    if ((fp = fopen("test1.txt", "r")) == NULL) {
        printf("Cannot open file.\n");
        exit(1);
    }

    i = 0;
    while (fscanf(fp, "%f %f %d", &x[i], &y[i], &outputs[i]) != EOF) {
        if (outputs[i] == 0) {
            outputs[i] = -1;
        }
        i++;
    }
    patternCount = i;

    weights[0] = randomFloat();
    weights[1] = randomFloat();
    weights[2] = randomFloat();

    iteration = 0;
    do {
        iteration++;
        globalError = 0;
        for (p = 0; p < patternCount; p++) {
            output = calculateOutput(weights, x[p], y[p]);

            localError = outputs[p] - output;
            weights[0] += LEARNING_RATE * localError * x[p];
            weights[1] += LEARNING_RATE * localError * y[p];
            weights[2] += LEARNING_RATE * localError;

            globalError += (localError*localError);
        }

        /* Root Mean Squared Error */
        printf("Iteration %d : RMSE = %.4f\n", iteration,
               sqrt(globalError/patternCount));
    } while (globalError != 0 && iteration<=MAX_ITERATION);

    printf("\nDecision boundary (line) equation: %.2f*x + %.2f*y + %.2f = 0\n",
           weights[0], weights[1], weights[2]);

    return 0;
}

这是我写的代码

   <?php
    define("LEARNING_RATE", 0.1);
    define("MAX_ITERATION", 100);
    function randomFloat(){ return (float) mt_rand() / mt_getrandmax(); }
    function calculateOutput($weights, $x, $y){
        $sum = (float) $x * $weights[0] + $y * $weights[1] + $weights[2];
        return ($sum >= 0) ? 1 : -1;
    }
    srand(time());
    $i = 0;
    $ars = explode("\n",file_get_contents('https://raw.githubusercontent.com/RichardKnop/ansi-c-perceptron/master/test1.txt'));
    foreach($ars as $ar){
        $temp = explode("\t", $ar);
        $x[$i] = (float) $temp[0];
        $y[$i] = (float) $temp[1];
        $output[$i] = (int) $temp[2];
        if($output[$i] == 0)
            $output[$i] = -1;
        $i++;
   }
   $patternCount = $i;
   $weights[0] = randomFloat();
   $weights[1] = randomFloat();
   $weights[2] = randomFloat();
   $iteration = 0;
   do{
       $iteration++;
       $globalError = 0;
       for ($p = 0; $p < $patternCount; $p++) {
           $output = calculateOutput($weights, $x[$p], $y[$p]);
           $localError = $outputs[$p] - $output;
           $weights[0] += LEARNING_RATE * $localError * $x[$p];
           $weights[1] += LEARNING_RATE * $localError * $y[$p];
           $weights[2] += LEARNING_RATE * $localError;
           $globalError += ($localError*$localError);
       }
       $r .= "Iteration $iteration : RMSE = " . 
sqrt($globalError/$patternCount)."<br>";
}while($globalError != 0 && $iteration<=MAX_ITERATION);
echo $r;
echo "<br><hr><br>";
echo "Decision boundary (line) equation: ".$weights[0]."*x + ".$weights[1]."*y + ".$weights[2]." = 0<br>";

它实际上是相同的，但为什么它不起作用？

标签： phpcneural-networkartificial-intelligence

解决方案

    $ars = explode("\n",file_get_contents('…'));

由于文件以 a 结尾\n，这会产生一个空字符串作为最后一个数组值，这会破坏foreach($ars as $ar)循环。要将文件读入数组，只需使用：

    $ars = file('…');

在foreach($ars as $ar)循环中，您使用了错误的名称$output[$i]而不是$outputs[$i].

       $r .= "Iteration $iteration : RMSE = " . 
sqrt($globalError/$patternCount)."<br>";
}while($globalError != 0 && $iteration<=MAX_ITERATION);
echo $r;

你没有初始化$r。代替上述方法，您可以使用：

       echo "Iteration $iteration : RMSE = " . 
            sqrt($globalError/$patternCount)."<br>";
    } while ($globalError != 0 && $iteration<=MAX_ITERATION);

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