java代码写算法 根据算法写代码

用Java写一个算法,把一串数字,所有可能的和按顺序排列,并计算每个和出现的次数

楼主你好

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应你的要求 我只做了加一位的和加两位的

算法类代码如下:

public class CountSumClass {

private String number;

private String result = new String("");

public CountSumClass() {

number = new String();

}

public CountSumClass(String str) {

number = str;

}

public String getResult() {

return result;

}

public void addOne() {

int x,y;

for (int i = 0; i number.length()-1; i++) {

x = (int)number.charAt(i) - 48;

for(int j = i+1; jnumber.length(); j++) {

y = (int)number.charAt(j) - 48;

result += x+"+"+y+"="+(x+y)+"\n";

}

}

y=0;

for (int i = 0; inumber.length(); i++) {

x = (int)number.charAt(i) - 48;

y += x;

if(i == number.length()- 1) {

result += x+"="+y;

} else {

result += x+"+";

}

}

}

public void addTwo() {

int x,y,z;

result += "\n";

for (int i = 0; inumber.length()-1; i++) {

String substr = number.substring(i,i+2);

x = Integer.parseInt(substr);

z = (x%10) * 10 + (x/10);

for(int j=0; jnumber.length(); j++) {

if(j!=i j!=i+1) {

y = (int)number.charAt(j) - 48;

result += x+"+"+y+"="+(x+y)+"\n";

result += z+"+"+y+"="+(z+y)+"\n";

}

}

}

}

public String toString() {

return result;

}

}

希望能帮助你哈

JAVA 实现算法

package huda.laogao.ON_20121216;

import java.util.*;

public class GetEquation {

ArrayListInteger params = null;// 进行加减的数,长度设为n

int result = 0;// 结果

public GetEquation(ArrayListInteger params, int result) {

this.params = params;

this.result = result;

}

public void run() {

int size = params.size();

if (size == 1) {

if (params.get(0) == result)

System.out.println(result + "=" + result);

else

System.out.println("Invalid");

return;

}

int[][] matrix = getMatrix(size - 1);

int m = matrix.length;// 行数

int count = 0;// 记录符合结果的组合数

for (int i = 0; i m; i++) {

int now = params.get(0);// 进行加减的结果,初始为第一个值

// 从第二个数开始进行加或减,加的话就相当于该数乘上1,然后加到结果上,

// 减的就相当于该数乘上-1,然后加到结果上

for (int j = 1; j size; j++) {

now += matrix[i][j - 1] * params.get(j);

}

// System.out.println(now);

// 判断结果

if (now == result) {

count++;// 组合数加1

System.out.print(params.get(0));

for (int j = 1; j size; j++) {

if (matrix[i][j - 1] == 1)

System.out.print("+" + params.get(j));

else

System.out.print("-" + params.get(j));

}// for j

System.out.println("=" + result);

}// if

}// for i

if (count == 0)

System.out.println("Invalid");

}

public int[][] getMatrix(int n) {

int m = (int) Math.pow(2, n);

int matrix[][] = new int[m][n];

for (int i = 0; i n; i++) {

int num = (int) Math.pow(2, i + 1);

// 总共分 2^(i+1)块,如i=0,即该矩阵的第一列,可分为2块,上一块取1,下一块取-1

int size = (int) Math.pow(2, n - i - 1);

// 每块的大小为2^(n-i-1),如n=3,i=0,每块的大小为4,即前4个为1,后4个为-1

int flag = 1;// 先为+

for (int j = 0; j num; j++) {

for (int k = 0; k size; k++) {

matrix[k + j * size][i] = flag;

}

flag *= -1;

}

}

return matrix;

}

public void print(int[][] matrix) {

for (int i = 0; i matrix.length; i++) {

for (int j = 0; j matrix[i].length; j++) {

System.out.print(matrix[i][j] + "\t");

}

System.out.println();

}

}

public static void main(String args[]) {

ArrayListInteger params = new ArrayListInteger();

params.add(1);

params.add(2);

params.add(3);

params.add(4);

int result = 10;

GetEquation ge = new GetEquation(params, result);

ge.run();

}

}

运行结果为:1+2+3+4=10

注:难点为获取加减矩阵,可辅助print()函数帮助理解

望采纳

如何用70行Java代码实现深度神经网络算法

参考下面代码:

import java.util.Random;

public class BpDeep{

public double[][] layer;//神经网络各层节点

public double[][] layerErr;//神经网络各节点误差

public double[][][] layer_weight;//各层节点权重

public double[][][] layer_weight_delta;//各层节点权重动量

public double mobp;//动量系数

public double rate;//学习系数

public BpDeep(int[] layernum, double rate, double mobp){

this.mobp = mobp;

this.rate = rate;

layer = new double[layernum.length][];

layerErr = new double[layernum.length][];

layer_weight = new double[layernum.length][][];

layer_weight_delta = new double[layernum.length][][];

Random random = new Random();

for(int l=0;llayernum.length;l++){

layer[l]=new double[layernum[l]];

layerErr[l]=new double[layernum[l]];

if(l+1layernum.length){

layer_weight[l]=new double[layernum[l]+1][layernum[l+1]];

layer_weight_delta[l]=new double[layernum[l]+1][layernum[l+1]];

for(int j=0;jlayernum[l]+1;j++)

for(int i=0;ilayernum[l+1];i++)

layer_weight[l][j][i]=random.nextDouble();//随机初始化权重

}

}

}

//逐层向前计算输出

public double[] computeOut(double[] in){

for(int l=1;llayer.length;l++){

for(int j=0;jlayer[l].length;j++){

double z=layer_weight[l-1][layer[l-1].length][j];

for(int i=0;ilayer[l-1].length;i++){

layer[l-1][i]=l==1?in[i]:layer[l-1][i];

z+=layer_weight[l-1][i][j]*layer[l-1][i];

}

layer[l][j]=1/(1+Math.exp(-z));

}

}

return layer[layer.length-1];

}

//逐层反向计算误差并修改权重

public void updateWeight(double[] tar){

int l=layer.length-1;

for(int j=0;jlayerErr[l].length;j++)

layerErr[l][j]=layer[l][j]*(1-layer[l][j])*(tar[j]-layer[l][j]);

while(l--0){

for(int j=0;jlayerErr[l].length;j++){

double z = 0.0;

for(int i=0;ilayerErr[l+1].length;i++){

z=z+l0?layerErr[l+1][i]*layer_weight[l][j][i]:0;

layer_weight_delta[l][j][i]= mobp*layer_weight_delta[l][j][i]+rate*layerErr[l+1][i]*layer[l][j];//隐含层动量调整

layer_weight[l][j][i]+=layer_weight_delta[l][j][i];//隐含层权重调整

if(j==layerErr[l].length-1){

layer_weight_delta[l][j+1][i]= mobp*layer_weight_delta[l][j+1][i]+rate*layerErr[l+1][i];//截距动量调整

layer_weight[l][j+1][i]+=layer_weight_delta[l][j+1][i];//截距权重调整

}

}

layerErr[l][j]=z*layer[l][j]*(1-layer[l][j]);//记录误差

}

}

}

public void train(double[] in, double[] tar){

double[] out = computeOut(in);

updateWeight(tar);

}

}


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