不要62 HDU - 2089

杭州的士车牌号算法
本文介绍了一种算法,用于计算杭州交通管理局发放不含特定不吉利数字(如4或62连续出现)的新出租车车牌数量。通过对输入区间的处理,算法能够准确计算出符合要求的车牌号总数。

杭州人称那些傻乎乎粘嗒嗒的人为62(音:laoer)。 
杭州交通管理局经常会扩充一些的士车牌照,新近出来一个好消息,以后上牌照,不再含有不吉利的数字了,这样一来,就可以消除个别的士司机和乘客的心理障碍,更安全地服务大众。 
不吉利的数字为所有含有4或62的号码。例如: 
62315 73418 88914 
都属于不吉利号码。但是,61152虽然含有6和2,但不是62连号,所以不属于不吉利数字之列。 
你的任务是,对于每次给出的一个牌照区间号,推断出交管局今次又要实际上给多少辆新的士车上牌照了。 

Input

输入的都是整数对n、m(0<n≤m<1000000),如果遇到都是0的整数对,则输入结束。 

Output

对于每个整数对,输出一个不含有不吉利数字的统计个数,该数值占一行位置。 

Sample Input

1 100
0 0

Sample Output

80
#include <iostream>
#include <stdio.h>
#include <string.h>
#include <queue>

using namespace std;
int a[20];// 每一位的上限
int dp[20][20]; //记忆化
int dfs(int pos,int prev,int limit)
{//     当前第几位  数位条件   是否受上限
    int i;
    if(pos==0) return 1; 
    if(!limit&&dp[pos][prev] != -1) return dp[pos][prev];
    int up;
    int ans = 0;
    up = limit?a[pos]:9;
    for(i=0;i<=up;i++)
    {
        if(prev==6&&i==2) continue;
        if(i==4) continue;
        ans += dfs(pos-1,i,limit && i==up);
    }
    if(!limit) dp[pos][prev] = ans;
    return ans;
}

int solve(int x)
{
    int p = 0;
    while(x)
    {
        a[++p] = x%10;
        x /= 10;
    }
    return dfs(p,0,1);
}
int main()
{
    int l,r,i,j,m;
    while(scanf("%d%d",&l,&r) != EOF&&(l||r))
    {
        memset(dp,-1,sizeof(dp));
        int ans = solve(r) - solve(l-1);
        printf("%d\n",ans);
    }
    return 0;
}

 

### HDU OJ 2089 Problem Solution and Description The problem titled "不高兴的津津" (Unhappy Jinjin) involves simulating a scenario where one needs to calculate the number of days an individual named Jinjin feels unhappy based on certain conditions related to her daily activities. #### Problem Statement Given a series of integers representing different aspects of Jinjin's day, such as homework completion status, weather condition, etc., determine how many days she was not happy during a given period. Each integer corresponds to whether specific events occurred which could affect her mood positively or negatively[^1]. #### Input Format Input consists of multiple sets; each set starts with two positive integers n and m separated by spaces, indicating the total number of days considered and types of influencing factors respectively. Following lines contain details about these influences over those days until all cases are processed when both numbers become zero simultaneously. #### Output Requirement For every dataset provided, output should be formatted according to sample outputs shown below: ```plaintext Case k: The maximum times of appearance is x, the color is c. ``` Where `k` represents case index starting from 1, while `x` stands for frequency count and `c` denotes associated attribute like colors mentioned earlier but adapted accordingly here depending upon context i.e., reasons causing unhappiness instead[^2]. #### Sample Code Implementation Below demonstrates a simple approach using Python language to solve this particular challenge efficiently without unnecessary complexity: ```python def main(): import sys input = sys.stdin.read().strip() datasets = input.split('\n\n') results = [] for idx, ds in enumerate(datasets[:-1], start=1): data = list(map(int, ds.strip().split())) n, m = data[:2] if n == 0 and m == 0: break counts = {} for _ in range(m): factor_counts = dict(zip(data[2::2], data[3::2])) for key, value in factor_counts.items(): try: counts[key] += value except KeyError: counts[key] = value max_key = max(counts, key=lambda k:counts[k]) result_line = f'Case {idx}: The maximum times of appearance is {counts[max_key]}, the reason is {max_key}.' results.append(result_line) print("\n".join(results)) if __name__ == '__main__': main() ```
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