免疫蚁群算法python代码

以下是免疫蚁群算法的Python代码示例：

import numpy as np

# 初始化参数
num_ants = 10
num_iterations = 100
num_features = 5
num_clusters = 3
q0 = 0.9
beta = 1.0
rho = 0.1

# 生成数据
data = np.random.rand(100, num_features)

# 初始化信息素矩阵
pheromone = np.ones((num_features, num_clusters))

# 迭代
for i in range(num_iterations):
    # 初始化蚂蚁位置和聚类结果
    ant_positions = np.zeros(num_ants, dtype=int)
    ant_clusters = np.zeros(num_ants, dtype=int)
    
    # 蚂蚁选择聚类中心
    for j in range(num_ants):
        # 计算概率
        prob = np.power(pheromone[:, ant_clusters[j]], beta)
        prob /= np.sum(prob)
        
        # 选择聚类中心
        if np.random.rand() < q0:
            ant_positions[j] = np.argmax(prob)
        else:
            ant_positions[j] = np.random.choice(num_features, p=prob)
        
        # 更新聚类结果
        ant_clusters[j] = np.argmin(np.sum(np.power(data - data[ant_positions[j]], 2), axis=1))
    
    # 计算适应度函数值
    fitness = np.zeros(num_clusters)
    for j in range(num_clusters):
        fitness[j] = np.sum(np.power(data - data[ant_positions[j]], 2)[ant_clusters == j])
    
    # 更新信息素矩阵
    pheromone *= (1 - rho)
    for j in range(num_clusters):
        pheromone[:, j] += rho * (1 / fitness[j])