LA 3708 - Graveyard

本文深入探讨了AI音视频处理领域中的视频分割与语义识别技术,介绍了视频分割的基本概念、算法及其应用,并详细阐述了语义识别在自动驾驶、AR、SLAM等场景中的实现与优化策略。

Programming contests became so popular in the year 2397 that the governor of New Earck -- the largest human-inhabited planet of the galaxy -- opened a special Alley of Contestant Memories (ACM) at the local graveyard. The ACM encircles a green park, and holds the holographic statues of famous contestants placed equidistantly along the park perimeter. The alley has to be renewed from time to time when a new group of memorials arrives.

When new memorials are added, the exact place for each can be selected arbitrarily along the ACM, but the equidistant disposition must be maintained by moving some of the old statues along the alley.

Surprisingly, humans are still quite superstitious in 24th century: the graveyard keepers believe the holograms are holding dead people souls, and thus always try to renew the ACM with minimal possible movements of existing statues (besides, the holographic equipment is very heavy). Statues are moved along the park perimeter. Your work is to find a renewal plan which minimizes the sum of travel distances of all statues. Installation of a new hologram adds no distance penalty, so choose the places for newcomers wisely!

Input 

The input file contains several test cases, each of them consists of a a line that contains two integer numbers: n -- the number of holographic statues initially located at the ACM, and m -- the number of statues to be added (2$ \le$n$ \le$1000, 1$ \le$m$ \le$1000) . The length of the alley along the park perimeter is exactly 10 000 feet.

Output 

For each test case, write to the output a line with a single real number -- the minimal sum of travel distances of all statues (in feet). The answer must be precise to at least 4 digits after decimal point.

\epsfbox{p3708.eps}

Pictures show the first three examples. Marked circles denote original statues, empty circles denote new equidistant places, arrows denote movement plans for existing statues.

Sample Input 

2 1 
2 3 
3 1 
10 10

Sample Output 

1666.6667 
1000.0 
1666.6667 
0.0
#include <iostream>
#include <stdio.h>
#include <algorithm>
using namespace std;
const double LEN = 10000;
int main()
{
    int n, m, i, j;
    double l, nl, ans, p1, p2;
    while(scanf("%d%d",&n,&m)!=EOF)
    { 
      ans = 0;
      l = LEN/n;
      nl = LEN/(n+m);
      for(i=1, j=1; i<n; i++)
      {
               while( (l*i - j*nl) * (l*i - (j+1)*nl) > 1e-8)
               {
                      j++;
               }
               p1 = l*i - j*nl;
               p2 = (j+1)*nl - l*i;
             //  cout << p1 << " ***** " << p2 << endl;
               if(p1 < p2)
               {
                   ans += p1;
                   
               }else{
                   ans += p2;
                   
                   
               }
      }
      printf("%0.4f\n", ans);
    }
    return 0;
}

基于可靠性评估序贯蒙特卡洛模拟法的配电网可靠性评估研究(Matlab代码实现)内容概要:本文围绕“基于可靠性评估序贯蒙特卡洛模拟法的配电网可靠性评估研究”,介绍了利用Matlab代码实现配电网可靠性的仿真分析方法。重点采用序贯蒙特卡洛模拟法对配电网进行长时间段的状态抽样与统计,通过模拟系统元件的故障与修复过程,评估配电网的关键可靠性指标,如系统停电频率、停电持续时间、负荷点可靠性等。该方法能够有效处理复杂网络结构与设备时序特性,提升评估精度,适用于含分布式电源、电动汽车等新型负荷接入的现代配电网。文中提供了完整的Matlab实现代码与案例分析,便于复现和扩展应用。; 适合人群:具备电力系统基础知识和Matlab编程能力的高校研究生、科研人员及电力行业技术人员,尤其适合从事配电网规划、运行与可靠性分析相关工作的人员; 使用场景及目标:①掌握序贯蒙特卡洛模拟法在电力系统可靠性评估中的基本原理与实现流程;②学习如何通过Matlab构建配电网仿真模型并进行状态转移模拟;③应用于含新能源接入的复杂配电网可靠性定量评估与优化设计; 阅读建议:建议结合文中提供的Matlab代码逐段调试运行,理解状态抽样、故障判断、修复逻辑及指标统计的具体实现方式,同时可扩展至不同网络结构或加入更多不确定性因素进行深化研究。
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