智慧校园中的人工智能应用实践

def schedule_courses(courses, teachers, rooms):

import random

schedule = {}

for course in courses:

available_teachers = [t for t in teachers if t['availability']]

available_rooms = [r for r in rooms if r['availability']]

if not available_teachers or not available_rooms:

print("资源不足，无法安排课程")

return None

teacher = random.choice(available_teachers)

room = random.choice(available_rooms)

teacher['availability'] = False

room['availability'] = False

schedule[course] = {'teacher': teacher['name'], 'room': room['name']}

return schedule

courses = ['Math', 'Physics', 'Chemistry']

teachers = [{'name': 'Alice', 'availability': True}, {'name': 'Bob', 'availability': True}]

rooms = [{'name': 'Room1', 'availability': True}, {'name': 'Room2', 'availability': True}]

schedule = schedule_courses(courses, teachers, rooms)

print(schedule)

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import pandas as pd

# 示例数据集

data = {

'student_id': [1, 2, 3],

'hours_studied': [10, 5, 20],

'test_score': [70, 50, 90]

}

df = pd.DataFrame(data)

# 简单线性回归模型

from sklearn.linear_model import LinearRegression

X = df[['hours_studied']]

y = df['test_score']

model = LinearRegression()

model.fit(X, y)

# 预测新学生的成绩

new_student_hours = [[30]]

predicted_score = model.predict(new_student_hours)

print(f"预计该学生得分: {predicted_score[0]}")

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