题目标题: 高斯日记:Excel

大数学家高斯有个好习惯:无论如何都要记日记。

他的日记有个与众不同的地方,他从不注明年月日,而是用一个整数代替,比如:4210

后来人们知道,那个整数就是日期,它表示那一天是高斯出生后的第几天。这或许也是个好习惯,它时时刻刻提醒着主人:日子又过去一天,还有多少时光可以用于浪费呢?

高斯出生于:1777年4月30日。
   
    在高斯发现的一个重要定理的日记上标注着:5343,因此可算出那天是:1791年12月15日。

高斯获得博士学位的那天日记上标着:8113

请你算出高斯获得博士学位的年月日。

提交答案的格式是:yyyy-mm-dd, 例如:1980-03-21

请严格按照格式,通过浏览器提交答案。
注意:只提交这个日期,不要写其它附加内容,比如:说明性的文字。

题目描述:答案1799-07-16  用Excel处理 会比较简单

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标题: 马虎的算式:全排列

小明是个急性子,上小学的时候经常把老师写在黑板上的题目抄错了。

有一次,老师出的题目是:36 x 495 = ?

他却给抄成了:396 x 45 = ?

但结果却很戏剧性,他的答案竟然是对的!!

因为 36 * 495 = 396 * 45 = 17820

类似这样的巧合情况可能还有很多,比如:27 * 594 = 297 * 54

假设 a b c d e 代表1~9不同的5个数字(注意是各不相同的数字,且不含0)

能满足形如: ab * cde = adb * ce 这样的算式一共有多少种呢?

请你利用计算机的优势寻找所有的可能,并回答不同算式的种类数。

满足乘法交换律的算式计为不同的种类,所以答案肯定是个偶数。

答案直接通过浏览器提交。
注意:只提交一个表示最终统计种类数的数字,不要提交解答过程或其它多余的内容。

题目描述:全排列,然后注意去重,标记数组放在全局变量。

#include<iostream>
#include<algorithm>
#include<math.h>
#include<cstdio>
using namespace std;
int book[10][10][10][10][10]; int main(){
int cnt=0;
int a[9]={1,2,3,4,5,6,7,8,9};
do{
int x=(a[0]*10+a[1])*(a[2]*100+a[3]*10+a[4]);
int y=(a[0]*100+a[3]*10+a[1])*(a[2]*10+a[4]); if(book[a[0]][a[1]][a[2]][a[3]][a[4]]==0&&x==y){
book[a[0]][a[1]][a[2]][a[3]][a[4]]=1;
cout<<(a[0]*10+a[1])<<" "<<(a[2]*100+a[3]*10+a[4])<<endl;
cnt++;
}
}while(next_permutation(a,a+9));
cout<<cnt<<"\n";
return 0;
}

题目标题: 第39级台阶:递归

小明刚刚看完电影《第39级台阶》,离开电影院的时候,他数了数礼堂前的台阶数,恰好是39级!

站在台阶前,他突然又想着一个问题:

如果我每一步只能迈上1个或2个台阶。先迈左脚,然后左右交替,最后一步是迈右脚,也就是说一共要走偶数步。那么,上完39级台阶,有多少种不同的上法呢?

请你利用计算机的优势,帮助小明寻找答案。

要求提交的是一个整数。
注意:不要提交解答过程,或其它的辅助说明文字。

题目描述:用递归求解

#include<iostream>
#include<algorithm>
#include<math.h>
#include<cstdio>
using namespace std;
int cnt=0;
void dfs(int yu,int ci){ //yu 代表台阶剩余数 ci代表走的次数
if(ci>38||yu<0)return; //一定要加这个判断,否则容易爆栈
if(yu==0){
if(ci%2==0)cnt++;
}
dfs(yu-1,ci+1);
dfs(yu-2,ci+1);
}
int main(){
dfs(39,0);
cout<<cnt<<"\n";
return 0;
}

标题: 黄金连分数:高精度

黄金分割数0.61803... 是个无理数,这个常数十分重要,在许多工程问题中会出现。有时需要把这个数字求得很精确。

对于某些精密工程,常数的精度很重要。也许你听说过哈勃太空望远镜,它首次升空后就发现了一处人工加工错误,对那样一个庞然大物,其实只是镜面加工时有比头发丝还细许多倍的一处错误而已,却使它成了“近视眼”!!

言归正传,我们如何求得黄金分割数的尽可能精确的值呢?有许多方法。

比较简单的一种是用连分数:

1
    黄金数 = ---------------------
                        1
             1 + -----------------
                          1
                 1 + -------------
                            1
                     1 + ---------
                          1 + ...

这个连分数计算的“层数”越多,它的值越接近黄金分割数。

请你利用这一特性,求出黄金分割数的足够精确值,要求四舍五入到小数点后100位。

小数点后3位的值为:0.618
    小数点后4位的值为:0.6180
    小数点后5位的值为:0.61803
    小数点后7位的值为:0.6180340
   (注意尾部的0,不能忽略)

你的任务是:写出精确到小数点后100位精度的黄金分割值。

注意:尾数的四舍五入! 尾数是0也要保留!

显然答案是一个小数,其小数点后有100位数字,请通过浏览器直接提交该数字。
注意:不要提交解答过程,或其它辅助说明类的内容。

题目描述:

#include<stdio.h>
long long f[110],a[110];
int main(){
f[2]=1,f[1]=1;
int n=0;
for(int i=3;f[i]<1e18;i++){
f[i]=f[i-1]+f[i-2];
n++;
}
long long fz=f[58];
long long fm=f[59]; //58 59就可以 其他就不对
for(int i=0;i<101;i++){
int k=fz/fm;
printf("%d",k);
fz=(fz%fm)*10;
}
return 0;
}

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