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傳感與檢測實驗報告，差動變壓器的特性測定，江南大學物聯網自動化

taowen / 713人閱讀

摘要：線性回歸系數值線性回歸系數值用來記錄最大偏差尋找最大偏差最大偏差為求靈敏度靈敏度為求線性誤差非線性誤差為返回的系數公式返回常量系數系數公式求和求平方和返回對應項相乘后的和區間區間區間區間


public class LeastSquares {    public static void matching(double[] x, double[] y, double[] input, double fully) {        double k = getK(x, y);        double b = getB(x, y);        System.out.println("線性回歸系數k值：/t"+k+"/n" + "線性回歸系數b值：/t" + b);        double maxy = 0; //用來記錄最大偏差        //尋找最大偏差        for (int i = 0; i < input.length; i++) {            if (Math.abs(k * input[i] + b - y[i]) > maxy){                maxy = Math.abs(k * input[i] + b - y[i]);            }        }        System.out.println("最大偏差為：" + maxy);        //求靈敏度        double s = 0;        double sum = 0;        for (int i = 1; i < y.length; i++) {            sum += y[i] - y[i-1];        }        s = sum / (y.length - 1) / 20;        System.out.println("靈敏度為：" + s);        //求線性誤差        System.out.println("非線性誤差為：" + maxy/fully);    }    //返回x的系數k公式：k=( n sum( xy ) - sum( x ) sum( y ) )/( n sum( x^2 )-sum(x) ^ 2 )    public static double getK(double[] x, double[] y) {        int n = x.length;        return (double) ((n * pSum(x, y) - sum(x) * sum(y)) / (n * sqSum(x) - Math.pow(sum(x), 2)));    }//返回常量系數系數b 公式：b = sum( y ) / n - k * sum( x ) / n    public static double getB(double[] x, double[] y) {        int n = x.length;        double k = getK(x, y);        return sum(y) / n - k * sum(x) / n;    }//求和    private static double sum(double[] ds) {        double s = 0;        for (double d : ds) {            s = s + d;        }        return s;    }//求平方和    private static double sqSum(double[] ds) {        double s = 0;        for (double d : ds) {            s = (double) (s + Math.pow(d, 2));        }        return s;    }//返回對應項相乘后的和    private static double pSum(double[] x, double[] y) {        double s = 0;        for (int i = 0; i < x.length; i++) {            s = s + x[i] * y[i];        }        return s;    }    public static void main(String[] args) {        double[] x1 = {0,0.2,0.4,0.6,0.8,1.0};        double[] y1 = {17.6,73.6,133,200,256,312};        double[] inputs1 = x1;        double[] x2 = {0,-0.2,-0.4,-0.6,-0.8,-1.0};        double[] y2 = {40.0,96,152,208,264,328};        double[] inputs2 = x2;        double[] x3 = {0,0.2,0.4,0.6,0.8,1.0,1.2,1.4,1.6,1.8,2.0,2.2,2.4,2.6,2.8,3.0};        double[] y3 = {17.6,73.6,133,200,256,312,372,428,484,548,600,672,712,776,832,888};        double[] inputs3 = x3;        double[] x4 = {0,-0.2,-0.4,-0.6,-0.8,-1.0,-1.2,-1.4,-1.6,-1.8,-2.0,-2.2,-2.4,-2.6,-2.8,-3.0};        double[] y4 = {40.0,96,152,208,264,328,384,440,496,552,616,666,720,784,840,898};        double[] inputs4 = x4;        System.out.println("+1區間");        matching(x1, y1,inputs1,y1[y1.length-1]);        System.out.println("-1區間");        matching(x2, y2,inputs2,y2[y2.length-1]);        System.out.println("+3區間");        matching(x3, y3,inputs3,y3[y3.length-1]);        System.out.println("-3區間");        matching(x4, y4,inputs4,y4[y4.length-1]);    }}


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