Codeforces Round #290 (Div. 1)B. Fox And Jumping

在无限长的带状上,通过购买特定卡片实现从任一位置移动到任一位置的能力,并求解最小成本。每张卡片提供不同长度的跳跃能力与购买成本,挑战在于寻找成本最低的购买组合。
B. Fox And Jumping
time limit per test
2 seconds
memory limit per test
256 megabytes
input
standard input
output
standard output

Fox Ciel is playing a game. In this game there is an infinite long tape with cells indexed by integers (positive, negative and zero). At the beginning she is standing at the cell 0.

There are also n cards, each card has 2 attributes: length li and cost ci. If she pays ci dollars then she can apply i-th card. After applying i-th card she becomes able to make jumps of length li, i. e. from cell x to cell (x - li) or cell (x + li).

She wants to be able to jump to any cell on the tape (possibly, visiting some intermediate cells). For achieving this goal, she wants to buy some cards, paying as little money as possible.

If this is possible, calculate the minimal cost.

Input

The first line contains an integer n (1 ≤ n ≤ 300), number of cards.

The second line contains n numbers li (1 ≤ li ≤ 109), the jump lengths of cards.

The third line contains n numbers ci (1 ≤ ci ≤ 105), the costs of cards.

Output

If it is impossible to buy some cards and become able to jump to any cell, output -1. Otherwise output the minimal cost of buying such set of cards.

Sample test(s)
Input
3
100 99 9900
1 1 1
Output
2
Input
5
10 20 30 40 50
1 1 1 1 1
Output
-1
Input
7
15015 10010 6006 4290 2730 2310 1
1 1 1 1 1 1 10
Output
6
Input
8
4264 4921 6321 6984 2316 8432 6120 1026
4264 4921 6321 6984 2316 8432 6120 1026
Output
7237
Note

In first sample test, buying one card is not enough: for example, if you buy a card with length 100, you can't jump to any cell whose index is not a multiple of 100. The best way is to buy first and second card, that will make you be able to jump to any cell.

In the second sample test, even if you buy all cards, you can't jump to any cell whose index is not a multiple of 10, so you should output -1.


观察后可以发现,如果有a和b两张卡,那么我们可以每次都跳gcd(a, b)

如果要任意格子都能到,说明gcd == 1

于是问题转换成了得到k个数,它们的gcd==1 的最小代价

dp[i] 表示得到i的最小代价

数据有点大,改成用map来转移即可


/*************************************************************************
    > File Name: cf289b.cpp
    > Author: ALex
    > Mail: zchao1995@gmail.com 
    > Created Time: 2015年02月03日 星期二 02时05分37秒
 ************************************************************************/

#include <map>
#include <set>
#include <queue>
#include <stack>
#include <vector>
#include <cmath>
#include <cstdio>
#include <cstdlib>
#include <cstring>
#include <iostream>
#include <algorithm>
using namespace std;

const double pi = acos(-1);
const int inf = 0x3f3f3f3f;
const double eps = 1e-15;
typedef long long LL;
typedef pair <int, int> PLL;
map <int, int> dp;
const int N = 330;
int l[N], c[N];

int gcd (int a, int b)
{
	return b == 0 ? a : gcd (b, a % b);
}

int main ()
{
	int n;
	while (~scanf("%d", &n))
	{
		map <int, int> :: iterator it;
		for (int i = 1; i <= n; ++i)
		{
			scanf("%d", &l[i]);
		}
		for (int i = 1; i <= n; ++i)
		{
			scanf("%d", &c[i]);
		}
		dp.clear();
		dp[0] = 0;
		for (int i = 1; i <= n; ++i)
		{
			for (it = dp.begin(); it != dp.end(); ++it)
			{
				int t = gcd (l[i], it -> first);
				if (dp.count (t))
				{
					dp[t] = min (dp[t], it -> second + c[i]);
				}
				else
				{
					dp[t] = it -> second + c[i];
				}
			}
		}
		if (!dp.count (1))
		{
			printf("-1\n");
		}
		else
		{
			printf("%d\n", dp[1]);
		}
	}
	return 0;
}


农业作物成熟度实例分割数据集 一、基础信息 • 数据集名称:农业作物成熟度实例分割数据集 • 图片数量: 训练集:563张图片 验证集:161张图片 测试集:80张图片 总计:804张图片 • 训练集:563张图片 • 验证集:161张图片 • 测试集:80张图片 • 总计:804张图片 • 分类类别: bfullyripened: b类作物完全成熟状态 bgreen: b类作物绿色未成熟状态 bhalfripened: b类作物半成熟状态 lfullyripened: l类作物完全成熟状态 lgreen: l类作物绿色未成熟状态 lhalfripened: l类作物半成熟状态 • bfullyripened: b类作物完全成熟状态 • bgreen: b类作物绿色未成熟状态 • bhalfripened: b类作物半成熟状态 • lfullyripened: l类作物完全成熟状态 • lgreen: l类作物绿色未成熟状态 • lhalfripened: l类作物半成熟状态 • 标注格式:YOLO格式,包含实例分割多边形点标注,适用于实例分割任务。 • 数据格式:图片来源于农业图像数据库,细节清晰,适用于模型训练。 二、适用场景 • 农业AI监测系统开发:数据集支持实例分割任务,帮助构建能够自动识别作物部分并分类成熟度的AI模型,辅助农民进行精准农业管理。 • 精准农业应用研发:集成至农业智能平台,提供实时作物状态识别功能,优化灌溉、施肥和收获时间。 • 学术研究与创新:支持农业科学与人工智能交叉领域的研究,助力发表高水平农业AI论文。 • 农业教育与培训:数据集可用于农业院校或培训机构,作为学生学习作物识别和成熟度评估的重要资源。 三、数据集优势 • 精准标注与多样性:每张图片均经过精确标注,确保实例分割边界准确,类别分类正确。涵盖两种作物类型(b和l)和三种成熟度状态(完全成熟、绿色未成熟、半成熟),具有高度多样性,提升模型泛化能力。 • 任务适配性强:标注兼容主流深度学习框架(如YOLO等),可直接加载使用,支持实例分割任务,并可扩展到其他计算机视觉任务。 • 农业价值突出:专注于作物成熟度检测,为智能农业、自动化收获和作物健康监测提供关键数据支持,具有重要的实际应用价值。
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