PAT A1046 Shortest Distance

本文介绍了一个算法问题,即计算高速公路形成简单环形上的任意两个出口之间的最短距离。输入包括环形公路的出口数量和各段距离,以及若干对出口编号,任务是输出每对出口间的最短距离。解决方案采用预处理技术,避免了暴力算法的超时风险。

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The task is really simple: given N exits on a highway which forms a simple cycle, you are supposed to tell the shortest distance between any pair of exits.

Input Specification:
Each input file contains one test case. For each case, the first line contains an integer N (in [3,10
的五次方​​ ]), followed by N integer distances D​1​​ D​2​​ ⋯ D​N​​ , where D​i​​ is the distance between the i-th and the (i+1)-st exits, and D​N​​ is between the N-th and the 1st exits. All the numbers in a line are separated by a space. The second line gives a positive integer M (≤10的四次方​​ ), with M lines follow, each contains a pair of exit numbers, provided that the exits are numbered from 1 to N. It is guaranteed that the total round trip distance is no more than 10的7次方​​ .

Output Specification:
For each test case, print your results in M lines, each contains the shortest distance between the corresponding given pair of exits.

Sample Input:

5 1 2 4 14 9
3
1 3
2 5
4 1

Sample Output:

3
10
7

AC代码如下:

#include <stdio.h>
const int MAXN = 100010;
//dis[i]表示1号节点按顺时针方向到达i号节点的顺时针方向的下一个节点的距离
//A[i]表示i号与i+1号顶点的距离 

int main(int argc, char *argv[]) {
	int dis[MAXN],A[MAXN];  
	int sum = 0,query,n,i,t,left,right,temp;
	scanf("%d",&n);
	for(i=1;i<=n;i++){
		scanf("%d",&A[i]);
		sum+=A[i];   //累加sum
		dis[i]=sum;  //预处理dis数组 
	}
	scanf("%d",&query);
	for(i=0;i<query;i++){  //query个查询 
		scanf("%d%d",&left,&right);
		if(left>right){  //防止left>right 
			t=left;
			left=right;
			right=t;
		}  
		temp=dis[right-1]-dis[left-1];
		if(temp<(sum-temp)){
			printf("%d\n",temp);
		}
		else{
			printf("%d\n",sum-temp);
		}
	} 
	return 0;
}

注意:
1.不能使用暴力无脑算法,那样做会超时。
2.dis[i]表示1号节点按顺时针方向到达i号节点的顺时针方向的下一个节点的距离
3.A[i]表示i号与i+1号顶点的距离
4.dis数组和sum在读入的时候就可以累加得到,这样查询的时候其实就是dis[right-1]-[left-1],这样可以减少算法的时间复杂度。

内容概要:本文针对国内加密货币市场预测研究较少的现状,采用BP神经网络构建了CCi30指数预测模型。研究选取2018年3月1日至2019年3月26日共391天的数据作为样本,通过“试凑法”确定最优隐结点数目,建立三层BP神经网络模型对CCi30指数收盘价进行预测。论文详细介绍了数据预处理、模型构建、训练及评估过程,包括数据归一化、特征工程、模型架构设计(如输入层、隐藏层、输出层)、模型编译与训练、模型评估(如RMSE、MAE计算)以及结果可视化。研究表明,该模型在短期内能较准确地预测指数变化趋势。此外,文章还讨论了隐层节点数的优化方法及其对预测性能的影响,并提出了若干改进建议,如引入更多技术指标、优化模型架构、尝试其他时序模型等。 适合人群:对加密货币市场预测感兴趣的研究人员、投资者及具备一定编程基础的数据分析师。 使用场景及目标:①为加密货币市场投资者提供一种新的预测工具和方法;②帮助研究人员理解BP神经网络在时间序列预测中的应用;③为后续研究提供改进方向,如数据增强、模型优化、特征工程等。 其他说明:尽管该模型在短期内表现出良好的预测性能,但仍存在一定局限性,如样本量较小、未考虑外部因素影响等。因此,在实际应用中需谨慎对待模型预测结果,并结合其他分析工具共同决策。
Every year the cows hold an event featuring a peculiar version of hopscotch that involves carefully jumping from rock to rock in a river. The excitement takes place on a long, straight river with a rock at the start and another rock at the end, L units away from the start (1 ≤ L ≤ 1,000,000,000). Along the river between the starting and ending rocks, N (0 ≤ N ≤ 50,000) more rocks appear, each at an integral distance Di from the start (0 < Di < L). To play the game, each cow in turn starts at the starting rock and tries to reach the finish at the ending rock, jumping only from rock to rock. Of course, less agile cows never make it to the final rock, ending up instead in the river. Farmer John is proud of his cows and watches this event each year. But as time goes by, he tires of watching the timid cows of the other farmers limp across the short distances between rocks placed too closely together. He plans to remove several rocks in order to increase the shortest distance a cow will have to jump to reach the end. He knows he cannot remove the starting and ending rocks, but he calculates that he has enough resources to remove up to M rocks (0 ≤ M ≤ N). FJ wants to know exactly how much he can increase the shortest distance *before* he starts removing the rocks. Help Farmer John determine the greatest possible shortest distance a cow has to jump after removing the optimal set of M rocks. Input Line 1: Three space-separated integers: L, N, and M Lines 2..N+1: Each line contains a single integer indicating how far some rock is away from the starting rock. No two rocks share the same position. Output Line 1: A single integer that is the maximum of the shortest distance a cow has to jump after removing M rocks Sample Inputcopy Outputcopy 25 5 2 2 14 11 21 17 4 Hint Before removing any rocks, the shortest jump was a jump of 2 from 0 (the start) to 2. After removing the rocks at 2 and 14, the shortest required jump is a jump of 4 (from 17 to 21 or from 21 to 25).
07-24
To determine the greatest possible shortest distance a cow has to jump after removing the optimal set of M rocks, we can follow these steps: 1. Read the input values for L, N, and M. 2. Read the distances of the N rocks from the starting rock and store them in a list. 3. Sort the list of distances in ascending order. 4. Calculate the initial shortest jump as the distance from the starting rock to the first rock. 5. Initialize a variable max_jump to store the maximum shortest jump. 6. Iterate over each possible combination of removing M rocks from the list of distances. We can use a nested loop to generate all combinations. - For each combination, calculate the shortest jump after removing the selected rocks. - Update max_jump if the current shortest jump is greater than max_jump. 7. Print the value of max_jump as the maximum shortest distance a cow has to jump after removing M rocks. Here's an example implementation in Python: ```python from itertools import combinations L, N, M = map(int, input().split()) rocks = [] for _ in range(N): rocks.append(int(input())) rocks.sort() initial_jump = rocks[0] max_jump = 0 for remove_rocks in combinations(range(1, N + 1), M): jumps = [rocks[remove_rocks[i]] - rocks[remove_rocks[i - 1] - 1] for i in range(1, M)] jumps.append(L - rocks[remove_rocks[M - 1] - 1]) shortest_jump = min(jumps) max_jump = max(max_jump, shortest_jump) print(max_jump) ``` In the example input provided, the output would be `4`, which represents the maximum shortest distance a cow has to jump after removing 2 rocks. Note: This solution uses brute force to iterate over all possible combinations of removing M rocks. The time complexity is O(N choose M), which can be large for large values of N and M.
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