import numpy as np import pandas as pd import pickle

读取模型

with open('model.pkl', 'rb') as file: model = pickle.load(file)

weights1 = model['weights1'] weights2 = model['weights2'] bias1 = model['bias1'] bias2 = model['bias2']

读取新数据

pre_data = pd.read_excel('预测数据.xlsx') X_pre = pre_data[['接收距离（cm）', '热风速度(r/min)']].values

预测新数据

layer1_output_pre = sigmoid(np.dot(X_pre, weights1) + bias1) layer2_output_pre = sigmoid(np.dot(layer1_output_pre, weights2) + bias2)

print('Predicted Output:', layer2_output_pre)