使用邻接矩阵或者邻接表创建一个如下所示的无向图，并采用深度优先搜索和广度优先搜索2种遍历算法对图进行遍历。

以下是使用邻接矩阵和邻接表创建无向图，并采用深度优先搜索和广度优先搜索进行遍历的Python代码：

1. 邻接矩阵实现：

# 定义邻接矩阵
graph = [[0, 1, 1, 0, 0, 0],
         [1, 0, 0, 1, 1, 0],
         [1, 0, 0, 0, 1, 1],
         [0, 1, 0, 0, 0, 1],
         [0, 1, 1, 0, 0, 1],
         [0, 0, 1, 1, 1, 0]]

# 深度优先搜索
def dfs(graph, start, visited=None):
    if visited is None:
        visited = set()
    visited.add(start)
    print(start, end=' ')
    for i in range(len(graph[start])):
        if graph[start][i] and i not in visited:
            dfs(graph, i, visited)

# 广度优先搜索
def bfs(graph, start):
    visited, queue = set(), [start]
    visited.add(start)
    while queue:
        vertex = queue.pop(0)
        print(vertex, end=' ')
        for i in range(len(graph[vertex])):
            if graph[vertex][i] and i not in visited:
                visited.add(i)
                queue.append(i)

# 测试
print("邻接矩阵实现的无向图：")
for i in range(len(graph)):
    print(i, ':', end=' ')
    for j in range(len(graph[i])):
        if graph[i][j]:
            print(j, end=' ')
    print()

print("深度优先搜索结果：")
dfs(graph, 0)
print()

print("广度优先搜索结果：")
bfs(graph, 0)
print()

2. 邻接表实现：

# 定义邻接表
graph = {0: [1, 2],
         1: [0, 3, 4],
         2: [0, 4, 5],
         3: [1, 5],
         4: [1, 2, 5],
         5: [2, 3, 4]}

# 深度优先搜索
def dfs(graph, start, visited=None):
    if visited is None:
        visited = set()
    visited.add(start)
    print(start, end=' ')
    for i in graph[start]:
        if i not in visited:
            dfs(graph, i, visited)

# 广度优先搜索
def bfs(graph, start):
    visited, queue = set(), [start]
    visited.add(start)
    while queue:
        vertex = queue.pop(0)
        print(vertex, end=' ')
        for i in graph[vertex]:
            if i not in visited:
                visited.add(i)
                queue.append(i)

# 测试
print("邻接表实现的无向图：")
for k, v in graph.items():
    print(k, ':', v)

print("深度优先搜索结果：")
dfs(graph, 0)
print()

print("广度优先搜索结果：")
bfs(graph, 0)
print()