用c++自己确定一个简单无向图（顶点数>=5）利用邻接矩阵或者邻接表来实现图的构造，并完成: (1）用深度优先和广度优先两种算法对图进行遍历，输出顶点序列教据 (2）以合理的格式，输出各个顶点的邻接点。

在C++中，我们可以使用邻接矩阵或邻接表这两种数据结构来表示无向图。这里以邻接矩阵为例，因为它的操作效率适合于稠密图，即顶点间的边较多的情况。

#include <iostream>
#include <vector>

// 邻接矩阵实现
typedef std::vector<std::vector<int>> AdjMatrix;

AdjMatrix createAdjMatrix(int vertices) {
    AdjMatrix graph(vertices, std::vector<int>(vertices, 0)); // 初始化全零矩阵
    // 替换这里的代码，添加实际的边，例如：
    // graph[i][j] = 1; 表示顶点i和j之间有一条边
    return graph;
}

void depthFirstSearch(AdjMatrix& graph, int start) {
    std::vector<bool> visited(graph.size(), false);
    std::cout << "Depth First Search:\n";
    dfsUtil(graph, start, visited);
}

void dfsUtil(AdjMatrix& graph, int vertex, std::vector<bool>& visited) {
    visited[vertex] = true;
    std::cout << vertex << " ";
    
    for (int i = 0; i < graph.size(); ++i)
        if (!visited[i] && graph[vertex][i])
            dfsUtil(graph, i, visited);
}

void breadthFirstSearch(AdjMatrix& graph, int start) {
    std::vector<bool> visited(graph.size(), false);
    std::queue<int> queue;
    queue.push(start);

    std::cout << "Breadth First Search:\n";
    while (!queue.empty()) {
        int vertex = queue.front();
        queue.pop();
        visited[vertex] = true;
        
        std::cout << vertex << " ";
        
        for (int i = 0; i < graph.size(); ++i)
            if (!visited[i] && graph[vertex][i])
                queue.push(i);
    }
}

void printAdjacencyList(const AdjMatrix& graph) {
    for (int i = 0; i < graph.size(); ++i) {
        std::cout << "Adjacency list of vertex " << i << ":\n";
        for (int j = 0; j < graph.size(); ++j)
            if (graph[i][j]) {
                std::cout << j << " ";
            }
        std::cout << "\n";
    }
}

int main() {
    int vertices;
    std::cout << "Enter the number of vertices: ";
    std::cin >> vertices;

    AdjMatrix graph = createAdjMatrix(vertices);
    
    std::cout << "Enter the edges or adjacency matrix elements:\n"; // 这里添加输入边的逻辑

    depthFirstSearch(graph, 0); // 从顶点0开始深度优先搜索
    breadthFirstSearch(graph, 0); // 同样从顶点0开始广度优先搜索

    printAdjacencyList(graph);

    return 0;
}