【HDU 1087】Super Jumping! Jumping! Jumping!(最大上升子序列和,动态规划)

本文介绍了一款名为SuperJumping的游戏,并提供了一个算法解决方案来计算玩家在游戏中所能获得的最大得分。该算法采用动态规划的方法,确保从起点到终点的路径上所经过的所有棋子数值之和最大。

这里是题目

Super Jumping! Jumping! Jumping!
Time Limit: 2000/1000 MS (Java/Others) Memory Limit: 65536/32768 K (Java/Others)
Total Submission(s): 40411 Accepted Submission(s): 18655

Problem Description
Nowadays, a kind of chess game called “Super Jumping! Jumping! Jumping!” is very popular in HDU. Maybe you are a good boy, and know little about this game, so I introduce it to you now.

The game can be played by two or more than two players. It consists of a chessboard(棋盘)and some chessmen(棋子), and all chessmen are marked by a positive integer or “start” or “end”. The player starts from start-point and must jumps into end-point finally. In the course of jumping, the player will visit the chessmen in the path, but everyone must jumps from one chessman to another absolutely bigger (you can assume start-point is a minimum and end-point is a maximum.). And all players cannot go backwards. One jumping can go from a chessman to next, also can go across many chessmen, and even you can straightly get to end-point from start-point. Of course you get zero point in this situation. A player is a winner if and only if he can get a bigger score according to his jumping solution. Note that your score comes from the sum of value on the chessmen in you jumping path.
Your task is to output the maximum value according to the given chessmen list.

Input
Input contains multiple test cases. Each test case is described in a line as follow:
N value_1 value_2 …value_N
It is guarantied that N is not more than 1000 and all value_i are in the range of 32-int.
A test case starting with 0 terminates the input and this test case is not to be processed.

Output
For each case, print the maximum according to rules, and one line one case.

Sample Input
3 1 3 2
4 1 2 3 4
4 3 3 2 1
0

Sample Output
4
10
3

#include<stdio.h>
#include<string.h>
#include<math.h>
#include<algorithm>
using namespace std;
//dp[i]:以i结尾的数字可构成的最大和 
//   dp[i] = max(num[i] , dp[j:(1~i-1)] + num[i])      
int main()
{
    int n,a[1111];
    while(~scanf("%d",&n),n)
    {
        for(int i=0;i<n;i++)
        {
            scanf("%d",&a[i]);
        }
        int dp[1010];       //表示以i结尾的子串的最大和 
         int ans=0;
        for(int i=0;i<n;i++)
        {
            dp[i]=a[i];
            for(int j=0;j<i;j++)
            {
                if(a[i]>a[j])
                {
                    dp[i]=max(dp[i],dp[j]+a[i]);
                }
                ans=max(ans,dp[i]);
            }
        }
        printf("%d\n",ans);
    }
return 0;
}
个人防护装备实例分割数据集 一、基础信息 • 数据集名称:个人防护装备实例分割数据集 • 图片数量: 训练集:4524张图片 • 训练集:4524张图片 • 分类类别: 手套(Gloves) 头盔(Helmet) 未戴手套(No-Gloves) 未戴头盔(No-Helmet) 未穿鞋(No-Shoes) 未穿背心(No-Vest) 鞋子(Shoes) 背心(Vest) • 手套(Gloves) • 头盔(Helmet) • 未戴手套(No-Gloves) • 未戴头盔(No-Helmet) • 未穿鞋(No-Shoes) • 未穿背心(No-Vest) • 鞋子(Shoes) • 背心(Vest) • 标注格式:YOLO格式,适用于实例分割任务,包含边界框或多边形坐标。 • 数据格式:图片数据,来源于监控或相关场景。 二、适用场景 • 工业安全监控系统开发:用于自动检测工人是否佩戴必要的个人防护装备,提升工作场所安全性,减少工伤风险。 • 智能安防应用:集成到监控系统中,实时分析视频流,识别PPE穿戴状态,辅助安全预警。 • 合规性自动化检查:在建筑、制造等行业,自动检查个人防护装备穿戴合规性,支持企业安全审计。 • 计算机视觉研究:支持实例分割、目标检测等算法在安全领域的创新研究,促进AI模型优化。 三、数据集优势 • 类别全面:覆盖8种常见个人防护装备及其缺失状态,提供丰富的检测场景,确保模型能处理各种实际情况。 • 标注精准:采用YOLO格式,每个实例都经过精细标注,边界框或多边形坐标准确,提升模型训练质量。 • 真实场景数据:数据来源于实际环境,增强模型在真实世界中的泛化能力实用性。 • 兼容性强:YOLO格式便于与主流深度学习框架(如YOLO、PyTorch等)集成,支持快速部署实验。
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