CodeForces 518D---概率dp

本文通过动态规划方法解决了一个特定的电梯概率问题:在给定的时间内,计算一定数量的人上电梯的概率,并最终求出电梯上平均人数。文章详细解释了状态转移方程及其背后的逻辑。

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题意:

有 n 个人上电梯,每个人是否上电梯的概率是 p ,每个人不管是否上电梯都需要花费一秒,问 t 秒内,电梯上有多少人?(上了电梯

的人要一直在电梯上呆着)。


分析:

因为上了电梯的人要一直在电梯上呆着,因此用 dp[i][j] 表示第 i 秒第 j 个人上电梯的概率,初始dp[0][0]=1,当 n 个人全部上电梯以后,

此时时间已经不能影响概率:dp[i][j]=dp[i-1][j];当没全部上完电梯时,第 i 秒第 j 个人上电梯的概率等于上一秒他不上电梯的概率:

dp[i][j]=(1-p)*dp[i-1][j];所以第 i 秒第 j 个人上电梯的概率dp[i][j]+=p*dp[i-1][j-1],他上电梯的概率加上他之前上电梯的人的概率。


代码:

#include <bits/stdc++.h>
using namespace std;
//题意:上了电梯就不能下来
const int maxn=2000+10;
double dp[maxn][maxn];  ///dp[i][j]表示第i秒第j个人上电梯的概率
int main()
{
    int n,t;
    double p;
    cin >>n>>p>>t;
    dp[0][0]=1;
    for(int i=1;i<=t;i++)
    {
        for(int j=0;j<=n;j++)
        {
            if(j==n)
                dp[i][j]=dp[i-1][j]; //n个人上完了,概率不随时间改变
            else
                dp[i][j]=(1-p)*dp[i-1][j]; //后一秒上的概率等于前一秒他没上的概率
            if(j)
                dp[i][j]+=p*dp[i-1][j-1]; //第i秒第j个人上电梯的概率等于他上电梯的概率加上他之前的人上电梯的概率
        }
    }
    double ans=0;
    for(int i=1;i<=n;i++)
    {
        ans+=dp[t][i]*i; //第i个人上电梯的概率*i人
    }
    printf("%.7g\n",ans);
    return 0;
}
### Codeforces Problem 976C Solution in Python For solving problem 976C on Codeforces using Python, efficiency becomes a critical factor due to strict time limits aimed at distinguishing between efficient and less efficient solutions[^1]. Given these constraints, it is advisable to focus on optimizing algorithms and choosing appropriate data structures. The provided code snippet offers insight into handling string manipulation problems efficiently by customizing comparison logic for sorting elements based on specific criteria[^2]. However, for addressing problem 976C specifically, which involves determining the winner ('A' or 'B') based on frequency counts within given inputs, one can adapt similar principles of optimization but tailored towards counting occurrences directly as shown below: ```python from collections import Counter def determine_winner(): for _ in range(int(input())): count_map = Counter(input().strip()) result = "A" if count_map['A'] > count_map['B'] else "B" print(result) determine_winner() ``` This approach leverages `Counter` from Python’s built-in `collections` module to quickly tally up instances of 'A' versus 'B'. By iterating over multiple test cases through a loop defined by user input, this method ensures that comparisons are made accurately while maintaining performance standards required under tight computational resources[^3]. To further enhance execution speed when working with Python, consider submitting codes via platforms like PyPy instead of traditional interpreters whenever possible since they offer better runtime efficiencies especially important during competitive programming contests where milliseconds matter significantly.
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