POJ 1611 The Suspects

本文介绍了一个基于并查集数据结构的程序设计问题,该程序用于模拟非典在大学校园内的潜在传播路径。通过输入学生数量及他们参与的不同社团成员列表,程序能够计算出当一名学生被确认为疑似病例时,可能受感染的学生总数。

Description
Severe acute respiratory syndrome (SARS), an atypical pneumonia of unknown aetiology, was recognized as a global threat in mid-March 2003. To minimize transmission to others, the best strategy is to separate the suspects from others.
In the Not-Spreading-Your-Sickness University (NSYSU), there are many student groups. Students in the same group intercommunicate with each other frequently, and a student may join several groups. To prevent the possible transmissions of SARS, the NSYSU collects the member lists of all student groups, and makes the following rule in their standard operation procedure (SOP).
Once a member in a group is a suspect, all members in the group are suspects.
However, they find that it is not easy to identify all the suspects when a student is recognized as a suspect. Your job is to write a program which finds all the suspects.
Input
The input file contains several cases. Each test case begins with two integers n and m in a line, where n is the number of students, and m is the number of groups. You may assume that 0 < n <= 30000 and 0 <= m <= 500. Every student is numbered by a unique integer between 0 and n−1, and initially student 0 is recognized as a suspect in all the cases. This line is followed by m member lists of the groups, one line per group. Each line begins with an integer k by itself representing the number of members in the group. Following the number of members, there are k integers representing the students in this group. All the integers in a line are separated by at least one space.
A case with n = 0 and m = 0 indicates the end of the input, and need not be processed.
Output
For each case, output the number of suspects in one line.
Sample Input
100 4
2 1 2
5 10 13 11 12 14
2 0 1
2 99 2
200 2
1 5
5 1 2 3 4 5
1 0
0 0
Sample Output
4
1
1


题目大意:
有一个学校,有N个学生,编号为0-N-1,现在0号学生感染了非典,凡是和0在一个社团的人就会感染,并且这些人如果还参加了别的社团,他所在的社团照样全部感染,求感染的人数。
即求与0在一个并查集中的数目。
最后求ans时一定要用fnd()而不用f[]。


#include<algorithm>
#include<iostream>
#include<cstdio>
using namespace std;
int n,m,ans,f[30005];
int fnd(int x)
{
    if(f[x]!=x)
        f[x]=fnd(f[x]);
    return f[x];
}
int main()
{
    while(scanf("%d%d",&n,&m)&&(n||m))
    {
        ans=0;
        for(int i=0;i<=n-1;i++)
            f[i]=i;
        int k,x,y,f1,f2;
        while(m--)
        {
            scanf("%d",&k);
            for(int i=1;i<=k;i++)
            {
                scanf("%d",&x);
                if(i!=1)
                {
                    f1=fnd(x);
                    f2=fnd(y);
                    if(f1!=f2)
                        f[f1]=f2;
                }
                y=x;
            }
        }
        for(int i=0;i<=n-1;i++)
            if(fnd(i)==fnd(0))
                ans++;
        printf("%d\n",ans);
    }
    return 0;
}
考虑柔性负荷的综合能源系统低碳经济优化调度【考虑碳交易机制】(Matlab代码实现)内容概要:本文围绕“考虑柔性负荷的综合能源系统低碳经济优化调度”展开,重点研究在碳交易机制下如何实现综合能源系统的低碳化与经济性协同优化。通过构建包含风电、光伏、储能、柔性负荷等多种能源形式的系统模型,结合碳交易成本与能源调度成本,提出优化调度策略,以降低碳排放并提升系统运行经济性。文中采用Matlab进行仿真代码实现,验证了所提模型在平衡能源供需、平抑可再生能源波动、引导柔性负荷参与调度等方面的有效性,为低碳能源系统的设计与运行提供了技术支撑。; 适合人群:具备一定电力系统、能源系统背景,熟悉Matlab编程,从事能源优化、低碳调度、综合能源系统等相关领域研究的研究生、科研人员及工程技术人员。; 使用场景及目标:①研究碳交易机制对综合能源系统调度决策的影响;②实现柔性负荷在削峰填谷、促进可再生能源消纳中的作用;③掌握基于Matlab的能源系统建模与优化求解方法;④为实际综合能源项目提供低碳经济调度方案参考。; 阅读建议:建议读者结合Matlab代码深入理解模型构建与求解过程,重点关注目标函数设计、约束条件设置及碳交易成本的量化方式,可进一步扩展至多能互补、需求响应等场景进行二次开发与仿真验证。
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