HDU-1059-Dividing-多重背包

解决Marsha和Bill如何公平地分配不同价值的大理石集合问题。通过编程实现检查是否能将大理石分成两组,使得每组总价值相等。采用计数法进行算法设计。

Problem Description
Marsha and Bill own a collection of marbles. They want to split the collection among themselves so that both receive an equal share of the marbles. This would be easy if all the marbles had the same value, because then they could just split the collection in half. But unfortunately, some of the marbles are larger, or more beautiful than others. So, Marsha and Bill start by assigning a value, a natural number between one and six, to each marble. Now they want to divide the marbles so that each of them gets the same total value.
Unfortunately, they realize that it might be impossible to divide the marbles in this way (even if the total value of all marbles is even). For example, if there are one marble of value 1, one of value 3 and two of value 4, then they cannot be split into sets of equal value. So, they ask you to write a program that checks whether there is a fair partition of the marbles.

Input
Each line in the input describes one collection of marbles to be divided. The lines consist of six non-negative integers n1, n2, ..., n6, where ni is the number of marbles of value i. So, the example from above would be described by the input-line ``1 0 1 2 0 0''. The maximum total number of marbles will be 20000.

The last line of the input file will be ``0 0 0 0 0 0''; do not process this line.

Output
For each colletcion, output ``Collection #k:'', where k is the number of the test case, and then either ``Can be divided.'' or ``Can't be divided.''.

Output a blank line after each test case.

Sample Input
1 0 1 2 0 0 1 0 0 0 1 1 0 0 0 0 0 0

Sample Output
Collection #1: Can't be divided. Collection #2: Can be divided.

对于这种重量和价值相等的问题,还是继续用计数法。


#include <iostream>
#include <string.h>
#include <stdio.h>
using namespace std;
int arr[7], opt[120000], cnts[120000];
int main() {
	//freopen("in.txt","r",stdin);
	int c=0;
	while (true) {
		c++;
		int cnt = 0, sum = 0;
		for (int i = 1; i <= 6; i++) {
			cin >> arr[i];
			if (arr[i] == 0)
				cnt++;
			else
				sum += arr[i] * i;
		}
		if (cnt == 6)
			break;
		if (sum % 2) {
			printf("Collection #%d:\nCan't be divided.\n\n",c);
			continue;
		}
		sum >>= 1; //初2
		memset(opt, 0, sizeof(int) * (sum + 1));
		for (int i = 1; i <= 6; i++) {
			if(arr[i] == 0) continue;
			memset(cnts, 0, sizeof(int) * (sum + 1));
			for (int j = i; j <= sum; j++) {
				if (opt[j] < opt[j - i] + i && cnts[j-i] < arr[i]) {
					opt[j] = opt[j - i] + i;
					cnts[j] = cnts[j - i] + 1;
				}
			}
		}
		if (opt[sum] != sum) {
			printf("Collection #%d:\nCan't be divided.\n\n",c);
		} else
			printf("Collection #%d:\nCan be divided.\n\n",c);
	}
	return 0;
}


基于数据驱动的 Koopman 算子的递归神经网络模型线性化,用于纳米定位系统的预测控制研究(Matlab代码实现)内容概要:本文围绕“基于数据驱动的Koopman算子的递归神经网络模型线性化”展开,旨在研究纳米定位系统的预测控制方法。通过结合数据驱动技术与Koopman算子理论,将非线性系统动态近似为高维线性系统,进而利用递归神经网络(RNN)建模并实现系统行为的精确预测。文中详细阐述了模型构建流程、线性化策略及在预测控制中的集成应用,并提供了完整的Matlab代码实现,便于科研人员复现实验、优化算法并拓展至其他精密控制系统。该方法有效提升了纳米级定位系统的控制精度与动态响应性能。; 适合人群:具备自动控制、机器学习或信号处理背景,熟悉Matlab编程,从事精密仪器控制、智能制造或先进控制算法研究的研究生、科研人员及工程技术人员。; 使用场景及目标:①实现非线性动态系统的数据驱动线性化建模;②提升纳米定位平台的轨迹跟踪与预测控制性能;③为高精度控制系统提供可复现的Koopman-RNN融合解决方案; 阅读建议:建议结合Matlab代码逐段理解算法实现细节,重点关注Koopman观测矩阵构造、RNN训练流程与模型预测控制器(MPC)的集成方式,鼓励在实际硬件平台上验证并调整参数以适应具体应用场景。
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