使用java创造一个简单的加法界面并写出代码

好的，以下是一个使用 Java 创建一个简单加法界面的示例代码：

import javax.swing.*;

public])
output_var['medium'] = fuzz.trimf(output_var.universe, [0, 5, 10])
output_var['high'] = fuzz.trimf(output_var.universe, [5, 10, 10])

# 定义模糊逻辑变换器
low_trans = fuzz.defuzz(output_var.universe, output_var['low'].mf, 'centroid')
medium_trans = fuzz.defuzz(output_var.universe, output_var['medium'].mf, 'centroid')
high_trans = fuzz.defuzz(output_var.universe, output_var['high'].mf, 'centroid')

# 将输入信号通过模糊逻辑变换器进行变换
input_signal = 7

if input_signal <= 5:
    output_signal = low_trans
elif input_signal >= 10:
    output_signal = high_trans
else:
    output_signal = medium_trans

# 通过PID控制器进行控制
# ...

4. 采用模糊自适应控制：

import skfuzzy as fuzz

# 定义输入和输出变量
input_var = fuzz.variable.Universe(np.arange(0, 11, 1))
output_var = fuzz.variable.Universe(np.arange(0, 11, 1))

# 定义输入和输出变量的隶属函数
input_var['low'] = fuzz.trimf(input_var.universe, [0, 0, 5])
input_var['medium'] = fuzz.trimf(input_var.universe, [0, 5, 10])
input_var['high'] = fuzz.trimf(input_var.universe, [5, 10, 10])

output_var['low'] = fuzz.trimf(output_var.universe, [0, 0, 5])
output_var['medium'] = fuzz.trimf(output_var.universe, [0, 5, 10])
output_var['high'] = fuzz.trimf(output_var.universe, [5, 10, 10])

# 定义反馈控制器
feedback = ctrl.Antecedent(np.arange(0, 11, 1), 'feedback')

# 定义反馈控制器的隶属函数
feedback['low'] = fuzz.trimf(feedback.universe, [0, 0, 5])
feedback['medium'] = fuzz.trimf(feedback.universe, [0, 5, 10])
feedback['high'] = fuzz.trimf(feedback.universe, [5, 10, 10])

# 定义模糊规则
rule1 = ctrl.Rule(antecedent=feedback['low'], consequent=output_var['low'])
rule2 = ctrl.Rule(antecedent=feedback['medium'], consequent=output_var['medium'])
rule3 = ctrl.Rule(antecedent=feedback['high'], consequent=output_var['high'])

# 定义模糊控制器
system = ctrl.ControlSystem(rules=[rule1, rule2, rule3], inputs=[input_var, feedback], outputs=[output_var])

# 定义控制器的反馈回路
feedback_ctrl = ctrl.ControlSystemSimulation(system)

# 控制器的主循环
for i in range(10):
    # 获取反馈信号
    feedback_signal = get_feedback_signal()
    
    # 设定反馈信号
    feedback_ctrl.input['feedback'] = feedback_signal
    
    # 设定输入信号
    input_signal = get_input_signal()
    
    # 模糊控制器输出
    output_signal = feedback_ctrl.compute(inputs=[input_signal])
    
    # 执行输出信号
    execute_output_signal(output_signal)
    
    # 反馈控制器的迭代
    feedback_ctrl.compute()