解题报告2479

Strategies
Time Limit: 1000MS Memory Limit: 65536K
Total Submissions: 2009 Accepted: 973

Description

Background
Bill, Steve and Linus participate in programming contests just like the one you're competing in right now. They have different strategies and we’d like to find out whose strategy is the best.
Problem
Bill simply solves the problems in the order he gets them from the contest organizers. Steve first reads all the problems and then solves them in increasing order of difficulty. Linus also reads all problems first, but he's quite ambitious and thus solves them in decreasing order of difficulty.
The difficulty of a problem is measured in minutes it takes the guys to solve it. We have collected statistics and we've consulted the oracle Larry so we know for all kinds of problems how long the guys will need. We have also found out that the three of them always need the same time for each problem (which depends on the difficulty of the problem), so they only differ by their strategies.
For several contests, we'd like you to tell us the winner, the number of problems he solved and his score. The score for a single problem is the time in minutes from start of the contest until you solve it. The overall score is the sum of scores of the problems you solved. The guys never make mistakes so you don't have to deal with penalties. The winner is the one who solved the most problems, and in case of a tie, the one with the lowest score. If there's still a tie, then they agree that Steve wins because he always brings delicious apple pie.

Input

The first line contains the number of scenarios. Each scenario describes one contest and its first line tells you how long the contest lasts (in minutes, from 30 to 1440) and the number of problems (from 3 to 24). In a second line you'll get the difficulties of the problems, as explained above they tell you how many minutes (from 1 to 600) the guys need in order to solve the problems.

Output

The output for every scenario begins with a line containing "Scenario #i:", where i is the number of the scenario starting at 1. Then print a single line telling who wins, the number of problems he solves and his score. Use the exact format as shown below in the sample output, even if the winner only solves 0 or 1 problems. Terminate the output for the scenario with a blank line.

Sample Input

2
180 6
23 42 170 33 7 19
60 2
43 17

Sample Output

Scenario #1:
Steve wins with 5 solved problems and a score of 288.

Scenario #2:
Steve wins with 2 solved problems and a score of 77.

Source

TUD Programming Contest 2005 (Training Session), Darmstadt, Germany
Bill,Steve,Linus:)
code:
内容概要:本文档围绕六自由度机械臂的ANN人工神经网络设计展开,涵盖正向与逆向运动学求解、正向动力学控制,并采用拉格朗日-欧拉法推导逆向动力学方程,所有内容均通过Matlab代码实现。同时结合RRT路径规划与B样条优化技术,提升机械臂运动轨迹的合理性与平滑性。文中还涉及多种先进算法与仿真技术的应用,如状态估计中的UKF、AUKF、EKF等滤波方法,以及PINN、INN、CNN-LSTM等神经网络模型在工程问题中的建模与求解,展示了Matlab在机器人控制、智能算法与系统仿真中的强大能力。; 适合人群:具备一定Ma六自由度机械臂ANN人工神经网络设计:正向逆向运动学求解、正向动力学控制、拉格朗日-欧拉法推导逆向动力学方程(Matlab代码实现)tlab编程基础,从事机器人控制、自动化、智能制造、人工智能等相关领域的科研人员及研究生;熟悉运动学、动力学建模或对神经网络在控制系统中应用感兴趣的工程技术人员。; 使用场景及目标:①实现六自由度机械臂的精确运动学与动力学建模;②利用人工神经网络解决传统解析方法难以处理的非线性控制问题;③结合路径规划与轨迹优化提升机械臂作业效率;④掌握基于Matlab的状态估计、数据融合与智能算法仿真方法; 阅读建议:建议结合提供的Matlab代码进行实践操作,重点理解运动学建模与神经网络控制的设计流程,关注算法实现细节与仿真结果分析,同时参考文中提及的多种优化与估计方法拓展研究思路。
内容概要:本文围绕电力系统状态估计中的异常检测与分类展开,重点介绍基于Matlab代码实现的相关算法与仿真方法。文章详细阐述了在状态估计过程中如何识别和分类量测数据中的异常值,如坏数据、拓扑错误和参数误差等,采用包括残差分析、加权最小二乘法(WLS)、标准化残差检测等多种经典与现代检测手段,并结合实际算例验证方法的有效性。同时,文档提及多种状态估计算法如UKF、AUKF、EUKF等在负荷突变等动态场景下的应用,强调异常处理对提升电力系统运行可靠性与安全性的重要意义。; 适合人群:具备电力系统基础知识和一定Matlab编程能力的高校研究生、科研人员及从事电力系【状态估计】电力系统状态估计中的异常检测与分类(Matlab代码实现)统自动化相关工作的工程技术人员。; 使用场景及目标:①掌握电力系统状态估计中异常数据的产生机制与分类方法;②学习并实现主流异常检测算法,提升对状态估计鲁棒性的理解与仿真能力;③服务于科研项目、课程设计或实际工程中的数据质量分析环节; 阅读建议:建议结合文中提供的Matlab代码进行实践操作,配合电力系统状态估计的基本理论进行深入理解,重点关注异常检测流程的设计逻辑与不同算法的性能对比,宜从简单案例入手逐步过渡到复杂系统仿真。
评论
添加红包

请填写红包祝福语或标题

红包个数最小为10个

红包金额最低5元

当前余额3.43前往充值 >
需支付:10.00
成就一亿技术人!
领取后你会自动成为博主和红包主的粉丝 规则
hope_wisdom
发出的红包
实付
使用余额支付
点击重新获取
扫码支付
钱包余额 0

抵扣说明:

1.余额是钱包充值的虚拟货币,按照1:1的比例进行支付金额的抵扣。
2.余额无法直接购买下载,可以购买VIP、付费专栏及课程。

余额充值