设计一个python程序，可以通过输入一个需要达到的最终分数，输出最优的底层kpi各值

以下是一个设计的示例程序，它可以帮助您通过输入最终需要达到的分数来输出最优的底层KPI值：

def adjust_kpi(target_score):
    # 定义初始的底层KPI值
    kpi1 = 50
    kpi2 = 50
    kpi3 = 50
    
    # 定义初始的分支板块权重和能力权重
    branch_weights = [0.2, 0.3, 0.5]
    ability_weights = [0.05, 0.1, 0.15, 0.3, 0.4]
    
    # 定义迭代次数和学习率
    iterations = 1000
    learning_rate = 0.01
    
    # 进行迭代调整
    for _ in range(iterations):
        # 根据当前的底层KPI值计算得分
        current_score = calculate_score(kpi1, kpi2, kpi3, branch_weights, ability_weights)
        
        # 计算与目标得分之间的差距
        diff = target_score - current_score
        
        # 根据差距和学习率调整底层KPI值
        kpi1 += learning_rate * diff * branch_weights[0] * ability_weights[0]
        kpi2 += learning_rate * diff * branch_weights[0] * ability_weights[1]
        kpi3 += learning_rate * diff * branch_weights[0] * ability_weights[2]
        
        # 防止超出取值范围
        kpi1 = max(0, min(100, kpi1))
        kpi2 = max(0, min(100, kpi2))
        kpi3 = max(0, min(100, kpi3))
    
    # 返回最优的底层KPI值
    return kpi1, kpi2, kpi3

def calculate_score(kpi1, kpi2, kpi3, branch_weights, ability_weights):
    # 根据底层KPI值和权重计算得分
    branch_scores = [kpi1, kpi2, kpi3]
    ability_scores = [kpi1, kpi2, kpi3, kpi1, kpi2]
    
    branch_score = sum(score * weight for score, weight in zip(branch_scores, branch_weights))
    ability_score = sum(score * weight for score, weight in zip(ability_scores, ability_weights))
    
    return branch_score + ability_score

# 输入目标分数
target_score = float(input("请输入目标分数："))

# 调用函数获取最优的底层KPI各值
kpi1, kpi2, kpi3 = adjust_kpi(target_score)

# 输出最优的底层KPI各值
print("最优的底层KPI各值：")
print("KPI1:", kpi1)
print("KPI2:", kpi2)
print("KPI3:", kpi3)

请注意，这只是一个示例程序，具体实现可能需要根据您的需求进行调整。此外，因为缺少具体的计算公式和数据，上述示例中的计算方式仅供参考，您可能需要根据实际情况进行修改。