java实现AHP ⾃⼰测试，误差很⼩
package com.shuzhi.ahp;
import java.math.BigDecimal;
import java.util.Arrays;
public class AHPComputeWeight {
/**
* @param args
*/
public static void main(String[] args) {
/** a为N*N矩阵 */
double[][] a = new double[][] {
/
*{1.00,5.00,3.00},
{0.20,1.00,0.33},
nginx部署前端项目
{0.33,3.00,1.00}*/
//{7.00, 0.14, 3.00,1.00 }
{1.00,0.33,0.20,0.33},
{3.00,1.00,0.33,1.00},
{5.00,3.00,1.00,3.00},
{3.00,1.00,0.33,1.00}
};
int N = a[0].length;
double[] weight = new double[N];
AHPComputeWeight instance = Instance();
instance.weight(a, weight, N);
System.out.String(weight));
}
// 单例
private static final AHPComputeWeight acw = new AHPComputeWeight();
// 平均随机⼀致性指针
private double[] RI = { 0.00, 0.00, 0.58, 0.90, 1.12, 1.21, 1.32, 1.41,
1.45, 1.49 };
// 随机⼀致性⽐率
private double CR = 0.0;
/
/ 最⼤特征值
private double lamta = 0.0;
/**
* 私有构造
*/
private AHPComputeWeight() {
}
/**
* 返回单例
*
* @return
*/
public static AHPComputeWeight getInstance() {
return acw;
}
/**
* 计算权重
*
* @param a
* @param weight
* @param N
*/
public void weight(double[][] a, double[] weight, int N) {
// 初始向量Wk
double[] w0 = new double[N];
for (int i = 0; i < N; i++) {
w0[i] = 1.0 / N;
}
// ⼀般向量W（k+1）
double[] w1 = new double[N];
// W（k+1）的归⼀化向量
double[] w2 = new double[N];
double sum = 1.0;
double d = 1.0;
// 误差
double delt = 0.00001;
while (d > delt) {
d = 0.0;
sum = 0;
// 获取向量
//int index = 0;
for (int j = 0; j < N; j++) {
double t = 0.0;
for (int l = 0; l < N; l++)
t += a[j][l] * w0[l];
// w1[j] = a[j][0] * w0[0] + a[j][1] * w0[1] + a[j][2] * w0[2];                w1[j] = t;
sum += w1[j];
}
// 向量归⼀化
for (int k = 0; k < N; k++) {
w2[k] = w1[k] / sum;
// 最⼤差值
d = Math.max(Math.abs(w2[k] - w0[k]), d);
// ⽤于下次迭代使⽤
w0[k] = w2[k];
}
}
// 计算矩阵最⼤特征值lamta，CI，RI
lamta = 0.0;
for (int k = 0; k < N; k++) {
lamta += w1[k] / (N * w0[k]);
}
double CI = (lamta - N) / (N - 1);
if (RI[N - 1] != 0) {
CR = CI / RI[N - 1];
CR = CI / RI[N - 1];
}
// 四舍五⼊处理
lamta = round(lamta, 3);
CI = round(CI, 3);
CR = round(CR, 3);
for (int i = 0; i < N; i++) {
w0[i] = round(w0[i], 4);
w1[i] = round(w1[i], 4);
w2[i] = round(w2[i], 4);
}
// 控制台打印输出
System.out.println("lamta=" + lamta);
System.out.println("CI=" + CI);
System.out.println("CR=" + CR);
// 控制台打印权重
System.out.println("w0[]=");
for (int i = 0; i < N; i++) {
System.out.print(w0[i] + " ");
}
System.out.println("");
System.out.println("w1[]=");
for (int i = 0; i < N; i++) {
System.out.print(w1[i] + " ");
}
System.out.println("");
System.out.println("w2[]=");
for (int i = 0; i < N; i++) {
weight[i] = w2[i];
System.out.print(w2[i] + " ");
}
System.out.println("");
}
/**
* 四舍五⼊
*
* @param v
* @param scale
* @return
*/
public double round(double v, int scale) {
if (scale < 0) {
throw new IllegalArgumentException(
"The scale must be a positive integer or zero");
}
BigDecimal b = new String(v));
BigDecimal one = new BigDecimal("1");
return b.divide(one, scale, BigDecimal.ROUND_HALF_UP).doubleValue();    }
/**
* 返回随机⼀致性⽐率
*
* @return
*/
public  double getCR() {
return CR;
}
}
}