hdoj 1070 milk

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,介绍了其在自动驾驶、AR增强现实等场景的应用,以及在实现过程中所涉及的关键算法与实践案例。


http://acm.hdu.edu.cn/showproblem.php?pid=1070

Milk

Time Limit: 2000/1000 MS (Java/Others)    Memory Limit: 65536/32768 K (Java/Others)
Total Submission(s): 13526    Accepted Submission(s): 3296


Problem Description
Ignatius drinks milk everyday, now he is in the supermarket and he wants to choose a bottle of milk. There are many kinds of milk in the supermarket, so Ignatius wants to know which kind of milk is the cheapest.

Here are some rules:
1. Ignatius will never drink the milk which is produced 6 days ago or earlier. That means if the milk is produced 2005-1-1, Ignatius will never drink this bottle after 2005-1-6(inclusive).
2. Ignatius drinks 200mL milk everyday.
3. If the milk left in the bottle is less than 200mL, Ignatius will throw it away.
4. All the milk in the supermarket is just produced today.

Note that Ignatius only wants to buy one bottle of milk, so if the volumn of a bottle is smaller than 200mL, you should ignore it.
Given some information of milk, your task is to tell Ignatius which milk is the cheapest.
 


Input
The input contains several test cases. The first line of the input is a single integer T which is the number of test cases. T test cases follow.
Each test case starts with a single integer N(1<=N<=100) which is the number of kinds of milk. Then N lines follow, each line contains a string S(the length will at most 100 characters) which indicate the brand of milk, then two integers for the brand: P(Yuan) which is the price of a bottle, V(mL) which is the volume of a bottle.
 


Output
For each test case, you should output the brand of the milk which is the cheapest. If there are more than one cheapest brand, you should output the one which has the largest volume.
 


Sample Input
  
2 2 Yili 10 500 Mengniu 20 1000 4 Yili 10 500 Mengniu 20 1000 Guangming 1 199 Yanpai 40 10000
 


Sample Output
  
Mengniu Mengniu
#include<stdio.h>
struct Things
{
	char S[200];
	double P;//单价要用double型,以为算每日消费时可能得到小数,不能只取整 
	int V;
}thing[200];
int main()
{
	int T,N,i,j,k;
	double M;
    scanf("%d",&T);
	while(T--)
	{
	      scanf("%d",&N);
		  for(i=0,j=0;i<N;i++)
		  {
		     scanf("%s %d %d",thing[j].S,&thing[j].P,&thing[j].V);
		     if(thing[j].V>=200)
		     j+=1;
		 }
		 //printf("%d#\n",j);
		 for(i=1,k=0,M=thing[0].P/(thing[0].V/200);i<j;i++)
		 {
		 	if(thing[i].V/200<=5)
		 	{
		 	   if(M>thing[i].P/(thing[i].V/200))
		 	   {
				  M=thing[i].P/(thing[i].V/200);
				  k=i;
			   }
			   if(M==thing[i].P/(thing[i].V/200)&&thing[i].V>thing[k].V)
			   {
			   	  k=i;
			   }
		    }
		    else if(thing[i].V/200>5)
		    {
		    	if(M>thing[i].P/5)
		    	{
		    		M=thing[i].P/5;
		    		k=i;
		    	}
		    }
		     
		 }
		 printf("%s\n",thing[k].S);
	}
	return 0;
}

提供了基于BP(Back Propagation)神经网络结合PID(比例-积分-微分)控制策略的Simulink仿真模型。该模型旨在实现对杨艺所著论文《基于S函数的BP神经网络PID控制器及Simulink仿真》中的理论进行实践验证。在Matlab 2016b环境下开发,经过测试,确保能够正常运行,适合学习和研究神经网络在控制系统中的应用。 特点 集成BP神经网络:模型中集成了BP神经网络用于提升PID控制器的性能,使之能更好地适应复杂控制环境。 PID控制优化:利用神经网络的自学习能力,对传统的PID控制算法进行了智能调整,提高控制精度和稳定性。 S函数应用:展示了如何在Simulink中通过S函数嵌入MATLAB代码,实现BP神经网络的定制化逻辑。 兼容性说明:虽然开发于Matlab 2016b,但理论上兼容后续版本,可能会需要调整少量配置以适配不同版本的Matlab。 使用指南 环境要求:确保你的电脑上安装有Matlab 2016b或更高版本。 模型加载: 下载本仓库到本地。 在Matlab中打开.slx文件。 运行仿真: 调整模型参数前,请先熟悉各模块功能和输入输出设置。 运行整个模型,观察控制效果。 参数调整: 用户可以自由调节神经网络的层数、节点数以及PID控制器的参数,探索不同的控制性能。 学习和修改: 通过阅读模型中的注释和查阅相关文献,加深对BP神经网络与PID控制结合的理解。 如需修改S函数内的MATLAB代码,建议有一定的MATLAB编程基础。
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