ModuleNotFoundError: No module named 'SwarmOptimizer'

很抱歉，我的代码中有误，`SwarmOptimizer`应该被替换成`PSO`。下面是纠正后的代码：

import numpy as np
import pandas as pd
from sklearn.preprocessing import StandardScaler
from sklearn.model_selection import train_test_split
from keras.models import Sequential
from keras.layers import Dense
from keras.optimizers import Adam
from pyswarms.keras import PSO # 修改这里

# 加载数据集
dataset = pd.read_csv('tomato_data.csv', header=None)
X = dataset.iloc[:, :-1].values
y = dataset.iloc[:, -1].values

# 数据预处理
sc = StandardScaler()
X = sc.fit_transform(X)

# 划分训练集和测试集
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=0)

# 构建神经网络模型
model = Sequential()
model.add(Dense(12, input_dim=8, activation='relu'))
model.add(Dense(12, activation='relu'))
model.add(Dense(12, activation='relu'))
model.add(Dense(1, activation='linear'))

# 配置模型优化器
opt = Adam(lr=0.01)
model.compile(loss='mse', optimizer=opt, metrics=['mse'])

# 训练模型
optimizer = PSO(n_particles=10, dimensions=16, options={'c1': 0.5, 'c2': 0.3, 'w': 0.9})
history = model.fit(X_train, y_train, batch_size=32, epochs=100, verbose=1, validation_data=(X_test, y_test), callbacks=[optimizer])

# 绘制训练集和测试集的MSE曲线
import matplotlib.pyplot as plt
plt.plot(history.history['mse'], label='train')
plt.plot(history.history['val_mse'], label='test')
plt.title('MSE')
plt.xlabel('Epoch')
plt.ylabel('MSE')
plt.legend()
plt.show()

请注意，如果您的环境中没有安装`pyswarms`库，您需要通过以下命令来安装它：

pip install pyswarms