博客
关于我
Avoid The Lakes
阅读量:623 次
发布时间:2019-03-13

本文共 1815 字,大约阅读时间需要 6 分钟。

Avoid The Lakes

Time Limit : 2000/1000ms (Java/Other)   Memory Limit : 131072/65536K (Java/Other)
Total Submission(s) : 190   Accepted Submission(s) : 106
Problem Description

Farmer John's farm was flooded in the most recent storm, a fact only aggravated by the information that his cows are deathly afraid of water. His insurance agency will only repay him, however, an amount depending on the size of the largest "lake" on his farm.

The farm is represented as a rectangular grid with N (1 ≤ N ≤ 100) rows and M (1 ≤ M ≤ 100) columns. Each cell in the grid is either dry or submerged, and exactlyK (1 ≤ K ≤ N × M) of the cells are submerged. As one would expect, a lake has a central cell to which other cells connect by sharing a long edge (not a corner). Any cell that shares a long edge with the central cell or shares a long edge with any connected cell becomes a connected cell and is part of the lake.

 
Input

* Line 1: Three space-separated integers: NM, and K

* Lines 2..K+1: Line i+1 describes one submerged location with two space separated integers that are its row and column: R and C

 
Output

* Line 1: The number of cells that the largest lake contains. 

 
Sample Input
3 4 53 22 23 12 31 1
 
Sample Output
4
 题解:相当于水池数目那题,只不过这个是找最大的水的个数;
代码:
1 #include
2 #include
3 int N,M,max,step; 4 int map[110][110]; 5 void dfs(int x,int y){ 6     if(!map[x][y]||x<0||x>=N||y<0||y>=M)return; 7     map[x][y]=0;step++; 8     if(step>max)max=step; 9     dfs(x+1,y);dfs(x-1,y);dfs(x,y+1),dfs(x,y-1);10 //    step--;map[x][y]=1;11     return;12 }13 int main(){14     int K,x,y;15     while(~scanf("%d%d%d",&N,&M,&K)){16         memset(map,0,sizeof(map));17         while(K--){18             scanf("%d%d",&x,&y);19             map[x-1][y-1]=1;20         }21         max=step=0;22         for(x=0;x

 

转载地址:http://wehaz.baihongyu.com/

你可能感兴趣的文章
Nitrux 3.8 发布!性能全面提升,带来非凡体验
查看>>
NiuShop开源商城系统 SQL注入漏洞复现
查看>>
NI笔试——大数加法
查看>>
NLog 自定义字段 写入 oracle
查看>>
NLog类库使用探索——详解配置
查看>>
NLP 基于kashgari和BERT实现中文命名实体识别(NER)
查看>>
NLP 模型中的偏差和公平性检测
查看>>
Vue3.0 性能提升主要是通过哪几方面体现的?
查看>>
NLP 项目:维基百科文章爬虫和分类【01】 - 语料库阅读器
查看>>
NLP_什么是统计语言模型_条件概率的链式法则_n元统计语言模型_马尔科夫链_数据稀疏(出现了词库中没有的词)_统计语言模型的平滑策略---人工智能工作笔记0035
查看>>
NLP三大特征抽取器:CNN、RNN与Transformer全面解析
查看>>
NLP学习笔记:使用 Python 进行NLTK
查看>>
NLP度量指标BELU真的完美么?
查看>>
NLP的不同研究领域和最新发展的概述
查看>>
NLP的神经网络训练的新模式
查看>>
NLP采用Bert进行简单文本情感分类
查看>>
NLP问答系统:使用 Deepset SQUAD 和 SQuAD v2 度量评估
查看>>
NLP项目:维基百科文章爬虫和分类【02】 - 语料库转换管道
查看>>
NLP:使用 SciKit Learn 的文本矢量化方法
查看>>
nmap 使用方法详细介绍
查看>>