珠海网站建设知识,阿里云空间如何装wordpress,asp.net mvc 统计网站流量数据,创新驱动发展战略的意义当涉及到常见的算法示例时#xff0c;以下是一些常见的 C 算法及其示例#xff1a;
1. **排序算法**#xff1a; - 冒泡排序 - 选择排序 - 插入排序 - 归并排序 - 堆排序 - 计数排序 - 桶排序 - 基数排序
2. **搜索算法**#xff1a; - 线性搜…当涉及到常见的算法示例时以下是一些常见的 C 算法及其示例
1. **排序算法** - 冒泡排序 - 选择排序 - 插入排序 - 归并排序 - 堆排序 - 计数排序 - 桶排序 - 基数排序
2. **搜索算法** - 线性搜索 - 二分查找 - 深度优先搜索DFS - 广度优先搜索BFS
3. **字符串处理算法** - 字符串反转 - 字符串查找 - 字符串替换 - 字符串拼接 - 字符串分割
4. **图算法** - 最短路径算法如 Dijkstra 算法、Floyd-Warshall 算法 - 最小生成树算法如 Prim 算法、Kruskal 算法 - 拓扑排序算法 - 深度优先搜索DFS和广度优先搜索BFS
5. **动态规划算法** - 斐波那契数列 - 背包问题 - 最长公共子序列问题 - 最长递增子序列问题
6. **贪心算法** - 部分背包问题 - 区间调度问题 - 霍夫曼编码
1. **冒泡排序** cpp #include iostream #include vector void bubbleSort(std::vectorint arr) { int n arr.size(); for (int i 0; i n-1; i) { for (int j 0; j n-i-1; j) { if (arr[j] arr[j1]) { std::swap(arr[j], arr[j1]); } } } } int main() { std::vectorint arr {64, 34, 25, 12, 22, 11, 90}; bubbleSort(arr); for (int num : arr) { std::cout num ; } return 0; }
2. **选择排序** cpp #include iostream #include vector void selectionSort(std::vectorint arr) { int n arr.size(); for (int i 0; i n-1; i) { int min_index i; for (int j i1; j n; j) { if (arr[j] arr[min_index]) { min_index j; } } std::swap(arr[i], arr[min_index]); } } int main() { std::vectorint arr {64, 25, 12, 22, 11}; selectionSort(arr); for (int num : arr) { std::cout num ; } return 0; }
3. **插入排序** cpp #include iostream #include vector void insertionSort(std::vectorint arr) { int n arr.size(); for (int i 1; i n; i) { int key arr[i]; int j i - 1; while (j 0 arr[j] key) { arr[j1] arr[j]; j--; } arr[j1] key; } } int main() { std::vectorint arr {12, 11, 13, 5, 6, 7}; insertionSort(arr); for (int num : arr) { std::cout num ; } return 0; }
4. **归并排序** cpp #include iostream #include vector void merge(std::vectorint arr, int l, int m, int r) { int n1 m - l 1; int n2 r - m; std::vectorint L(n1), R(n2); for (int i 0; i n1; i) L[i] arr[l i]; for (int j 0; j n2; j) R[j] arr[m 1 j]; int i 0, j 0, k l; while (i n1 j n2) { if (L[i] R[j]) { arr[k] L[i]; i; } else { arr[k] R[j]; j; } k; } while (i n1) { arr[k] L[i]; i; k; } while (j n2) { arr[k] R[j]; j; k; } } void mergeSort(std::vectorint arr, int l, int r) { if (l r) { int m l (r - l) / 2; mergeSort(arr, l, m); mergeSort(arr, m 1, r); merge(arr, l, m, r); } } int main() { std::vectorint arr {12, 11, 13, 5, 6, 7}; mergeSort(arr, 0, arr.size() - 1); for (int num : arr) { std::cout num ; } return 0; }
5. **堆排序** cpp #include iostream #include vector #include algorithm void heapify(std::vectorint arr, int n, int i) { int largest i; int l 2*i 1; int r 2*i 2; if (l n arr[l] arr[largest]) largest l; if (r n arr[r] arr[largest]) largest r; if (largest ! i) { std::swap(arr[i], arr[largest]); heapify(arr, n, largest); } } void heapSort(std::vectorint arr) { int n arr.size(); for (int i n / 2 - 1; i 0; i--) heapify(arr, n, i); for (int i n-1; i 0; i--) { std::swap(arr[0], arr[i]); heapify(arr, i, 0); } } int main() { std::vectorint arr {12, 11, 13, 5, 6, 7}; heapSort(arr); for (int num : arr) { std::cout num ; } return 0; } 1. **线性搜索** cpp #include iostream #include vector int linearSearch(std::vectorint arr, int target) { for (int i 0; i arr.size(); i) { if (arr[i] target) { return i; } } return -1; // 未找到目标值 } int main() { std::vectorint arr {2, 5, 7, 9, 12, 15}; int target 7; int index linearSearch(arr, target); if (index ! -1) { std::cout 目标值在数组中的索引为 index std::endl; } else { std::cout 未找到目标值。 std::endl; } return 0; }
2. **二分查找** cpp #include iostream #include vector int binarySearch(std::vectorint arr, int target) { int left 0, right arr.size() - 1; while (left right) { int mid left (right - left) / 2; if (arr[mid] target) { return mid; } else if (arr[mid] target) { left mid 1; } else { right mid - 1; } } return -1; // 未找到目标值 } int main() { std::vectorint arr {2, 5, 7, 9, 12, 15}; int target 7; int index binarySearch(arr, target); if (index ! -1) { std::cout 目标值在数组中的索引为 index std::endl; } else { std::cout 未找到目标值。 std::endl; } return 0; }
1. **最短路径算法 - Dijkstra算法** cpp #include iostream #include vector #include queue #include limits #define INF std::numeric_limitsint::max() void dijkstra(std::vectorstd::vectorstd::pairint, int graph, int start) { int n graph.size(); std::vectorint dist(n, INF); dist[start] 0; std::priority_queuestd::pairint, int, std::vectorstd::pairint, int, std::greaterstd::pairint, int pq; pq.push({0, start}); while (!pq.empty()) { int u pq.top().second; pq.pop(); for (auto edge : graph[u]) { int v edge.first; int weight edge.second; if (dist[v] dist[u] weight) { dist[v] dist[u] weight; pq.push({dist[v], v}); } } } for (int i 0; i n; i) { std::cout 从节点 start 到节点 i 的最短距禿 dist[i] std::endl; } } int main() { int n 5; std::vectorstd::vectorstd::pairint, int graph(n); graph[0].push_back({1, 4}); graph[0].push_back({2, 1}); graph[1].push_back({3, 1}); graph[2].push_back({1, 2}); graph[2].push_back({3, 5}); graph[3].push_back({4, 3}); dijkstra(graph, 0); return 0; }
2. **最小生成树算法 - Prim算法** cpp #include iostream #include vector #include queue #include limits #define INF std::numeric_limitsint::max() void prim(std::vectorstd::vectorstd::pairint, int graph) { int n graph.size(); std::vectorbool visited(n, false); std::vectorint dist(n, INF); dist[0] 0; std::priority_queuestd::pairint, int, std::vectorstd::pairint, int, std::greaterstd::pairint, int pq; pq.push({0, 0}); while (!pq.empty()) { int u pq.top().second; pq.pop(); visited[u] true; for (auto edge : graph[u]) { int v edge.first; int weight edge.second; if (!visited[v] dist[v] weight) { dist[v] weight; pq.push({dist[v], v}); } } } int minCost 0; for (int d : dist) { minCost d; } std::cout 最小生成树的总权值为 minCost std::endl; } int main() { int n 5; std::vectorstd::vectorstd::pairint, int graph(n); graph[0].push_back({1, 2}); graph[0].push_back({3, 6}); graph[1].push_back({0, 2}); graph[1].push_back({2, 3}); graph[1].push_back({3, 8}); graph[2].push_back({1, 3}); graph[3].push_back({0, 6}); graph[3].push_back({1, 8}); prim(graph); return 0; }
1. **部分背包问题** cpp #include iostream #include vector #include algorithm struct Item { int value; int weight; }; bool compare(Item a, Item b) { double ratio1 (double)a.value / a.weight; double ratio2 (double)b.value / b.weight; return ratio1 ratio2; } double fractionalKnapsack(int capacity, std::vectorItem items) { std::sort(items.begin(), items.end(), compare); double maxValue 0.0; for (const Item item : items) { if (capacity 0) { break; } int weightToAdd std::min(item.weight, capacity); maxValue weightToAdd * ((double)item.value / item.weight); capacity - weightToAdd; } return maxValue; } int main() { int capacity 50; std::vectorItem items {{60, 10}, {100, 20}, {120, 30}}; double maxTotalValue fractionalKnapsack(capacity, items); std::cout 最大总价值为 maxTotalValue std::endl; return 0; }
2. **区间调度问题** cpp #include iostream #include vector #include algorithm struct Interval { int start; int end; }; bool compareEnd(Interval a, Interval b) { return a.end b.end; } int intervalScheduling(std::vectorInterval intervals) { if (intervals.empty()) { return 0; } std::sort(intervals.begin(), intervals.end(), compareEnd); int count 1; int end intervals[0].end; for (int i 1; i intervals.size(); i) { if (intervals[i].start end) { count; end intervals[i].end; } } return count; } int main() { std::vectorInterval intervals {{1, 3}, {2, 4}, {3, 6}, {5, 7}, {8, 9}}; int minRooms intervalScheduling(intervals); std::cout 需要的最小会议室数量为 minRooms std::endl; return 0; }
