Good Bye 2015

一周特定日糖果储蓄计划:2016年全年糖果总数预测
本文介绍了一只名为Limak的小北极熊如何通过在2016年的特定日子储蓄糖果来展示其责任感。通过分析Limak选择的计划,我们计算了他一年中总共能保存多少糖果。具体而言,如果Limak选择在一周的某一天或一个月的某一天进行糖果储蓄,我们将探讨一年中他能积累多少糖果。

A. New Year and Days
time limit per test
2 seconds
memory limit per test
256 megabytes
input
standard input
output
standard output

Today is Wednesday, the third day of the week. What's more interesting is that tomorrow is the last day of the year 2015.

Limak is a little polar bear. He enjoyed this year a lot. Now, he is so eager to the coming year 2016.

Limak wants to prove how responsible a bear he is. He is going to regularly save candies for the entire year 2016! He considers various saving plans. He can save one candy either on some fixed day of the week or on some fixed day of the month.

Limak chose one particular plan. He isn't sure how many candies he will save in the 2016 with his plan. Please, calculate it and tell him.

Input

The only line of the input is in one of the following two formats:

  • "x of week" where x (1 ≤ x ≤ 7) denotes the day of the week. The 1-st day is Monday and the 7-th one is Sunday.
  • "x of month" where x (1 ≤ x ≤ 31) denotes the day of the month.
Output

Print one integer — the number of candies Limak will save in the year 2016.

Sample test(s)
Input
4 of week
Output
52
Input
30 of month
Output
11
Note

Polar bears use the Gregorian calendar. It is the most common calendar and you likely use it too. You can read about it on Wikipedia if you want to 。。. The week starts with Monday.

In the first sample Limak wants to save one candy on each Thursday (the 4-th day of the week). There are 52 Thursdays in the 2016. Thus, he will save 52 candies in total.

In the second sample Limak wants to save one candy on the 30-th day of each month. There is the 30-th day in exactly 11 months in the 2016 — all months but February. It means that Limak will save 11 candies in total.



#include <bits/stdc++.h>
using namespace std ;

int main()
{
    int day ;
    string str,str0,s="week";
    cin >> day >> str0 >> str ;
    
    if(!str.compare(s))   //week
        {
            if(day == 6)
                cout << "53" <<endl;
            else if(day ==5)
                cout << "53"<<endl;
            else
                cout << "52" << endl;

        }
   if(!str.compare("month")) 
    {
        if(day<=29)
            cout << "12"<<endl;
        else if(day<=30)
            cout << "11"<<endl;
        else  if(day ==31)
            cout << "7"<<endl;

    }
    return 0;

}


【无人机】基于改进粒子群算法的无人机路径规划研究[和遗传算法、粒子群算法进行比较](Matlab代码实现)内容概要:本文围绕基于改进粒子群算法的无人机路径规划展开研究,重点探讨了在复杂环境中利用改进粒子群算法(PSO)实现无人机三维路径规划的方法,并将其与遗传算法(GA)、标准粒子群算法等传统优化算法进行对比分析。研究内容涵盖路径规划的多目标优化、避障策略、航路点约束以及算法收敛性和寻优能力的评估,所有实验均通过Matlab代码实现,提供了完整的仿真验证流程。文章还提到了多种智能优化算法在无人机路径规划中的应用比较,突出了改进PSO在收敛速度和全局寻优方面的优势。; 适合人群:具备一定Matlab编程基础和优化算法知识的研究生、科研人员及从事无人机路径规划、智能优化算法研究的相关技术人员。; 使用场景及目标:①用于无人机在复杂地形或动态环境下的三维路径规划仿真研究;②比较不同智能优化算法(如PSO、GA、蚁群算法、RRT等)在路径规划中的性能差异;③为多目标优化问题提供算法选型和改进思路。; 阅读建议:建议读者结合文中提供的Matlab代码进行实践操作,重点关注算法的参数设置、适应度函数设计及路径约束处理方式,同时可参考文中提到的多种算法对比思路,拓展到其他智能优化算法的研究与改进中。
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