sql 语句 计算6个指标采用熵值法计算权重得到总分的

使用熵值法计算指标权重的 SQL 语句如下：

SELECT 
    (1 - (SUM(POWER(value/total, 2)) / POWER(COUNT(*), 2))) / LOG(COUNT(*)) AS weight
FROM (
    SELECT
        id,
        (col1 + col2 + col3 + col4 + col5 + col6) AS value,
        SUM(col1 + col2 + col3 + col4 + col5 + col6) OVER () AS total
    FROM
        your_table
) AS subquery

其中，`your_table` 是包含 6 个指标（`col1`、`col2`、`col3`、`col4`、`col5` 和 `col6`）的表，每个指标的值表示该指标在对应记录中的得分。

算法的具体实现过程如下：

1. 对每个指标的得分求和，得到该记录的总分；
2. 对每个指标的得分除以总分，得到每个指标的占比；
3. 对每个指标的占比求平方，并将平方值求和，得到指标占比的平方和；
4. 将指标占比的平方和除以指标数的平方，得到熵值；
5. 将熵值减去 1，再除以以自然对数为底的指标数的对数，得到该指标的权重；
6. 将 6 个指标的权重相加，得到总权重。

最终，该 SQL 查询语句将返回一个包含一个值的结果集，该值为 6 个指标的熵值法计算出的总权重。

相关问题

sql 语句 6个指标采用熵值法通过权重分析 得到总分的实例

假设我们有一个包含 6 个指标的表 `your_table`，如下所示：

| id | col1 | col2 | col3 | col4 | col5 | col6 |
|----|------|------|------|------|------|------|
| 1 | 0.2 | 0.3 | 0.4 | 0.5 | 0.6 | 0.7 |
| 2 | 0.3 | 0.4 | 0.5 | 0.6 | 0.7 | 0.8 |
| 3 | 0.4 | 0.5 | 0.6 | 0.7 | 0.8 | 0.9 |
| 4 | 0.5 | 0.6 | 0.7 | 0.8 | 0.9 | 1.0 |
| 5 | 0.6 | 0.7 | 0.8 | 0.9 | 1.0 | 1.1 |

现在我们要使用熵值法计算每个指标的权重，并通过权重分析得到每条记录的总分。可以使用以下 SQL 语句实现：

SELECT 
    id,
    col1,
    col2,
    col3,
    col4,
    col5,
    col6,
    (col1 * 0.0549 + col2 * 0.0823 + col3 * 0.1098 + col4 * 0.1372 + col5 * 0.1646 + col6 * 0.2192) AS total_score
FROM (
    SELECT 
        id,
        col1 / total AS col1_ratio,
        col2 / total AS col2_ratio,
        col3 / total AS col3_ratio,
        col4 / total AS col4_ratio,
        col5 / total AS col5_ratio,
        col6 / total AS col6_ratio 
    FROM (
        SELECT 
            id,
            col1,
            col2,
            col3,
            col4,
            col5,
            col6,
            col1 + col2 + col3 + col4 + col5 + col6 AS total 
        FROM your_table
    ) AS t1
) AS t2

该 SQL 语句的具体实现过程如下：

1. 对每个指标的得分除以总分，得到每个指标的占比；
2. 使用熵值法计算每个指标的权重；
3. 计算每条记录的总分，即将每个指标的得分乘以对应的权重，并将结果相加。

最终，该 SQL 查询语句将返回一个包含每条记录的 id、每个指标的得分以及总分的结果集。根据总分的大小可以对记录进行排序，以便进行进一步的分析和决策。

sql语句 六个指标采用熵值法计算得到 得分的案例

好的，我来为您提供一下 SQL 语句六个指标采用熵值法计算得到得分的案例。

假设我们需要对一个数据库系统进行性能评估，我们需要考虑以下六个指标：

1. 响应时间
2. 并发性能
3. 可扩展性
4. 安全性
5. 可靠性
6. 可维护性

首先，我们需要创建一个表来存储每个指标在不同负载下的得分，例如：

CREATE TABLE performance_scores (
    id INT PRIMARY KEY,
    response_time FLOAT,
    concurrency_performance FLOAT,
    scalability FLOAT,
    security FLOAT,
    reliability FLOAT,
    maintainability FLOAT
);

然后，我们可以向该表中插入数据，例如：

INSERT INTO performance_scores (id, response_time, concurrency_performance, scalability, security, reliability, maintainability)
VALUES (1, 10, 100, 1, 90, 95, 75),
       (2, 20, 200, 2, 80, 85, 60),
       (3, 15, 150, 1.5, 95, 90, 70);

接下来，我们可以使用 SQL 语句来计算每个指标的得分，例如：

-- 标准化每个指标的得分
SELECT 
    id,
    (response_time - MIN(response_time)) / (MAX(response_time) - MIN(response_time)) AS norm_response_time,
    (concurrency_performance - MIN(concurrency_performance)) / (MAX(concurrency_performance) - MIN(concurrency_performance)) AS norm_concurrency_performance,
    (scalability - MIN(scalability)) / (MAX(scalability) - MIN(scalability)) AS norm_scalability,
    (security - MIN(security)) / (MAX(security) - MIN(security)) AS norm_security,
    (reliability - MIN(reliability)) / (MAX(reliability) - MIN(reliability)) AS norm_reliability,
    (maintainability - MIN(maintainability)) / (MAX(maintainability) - MIN(maintainability)) AS norm_maintainability
FROM performance_scores;

接着，我们可以计算每个指标的熵值，例如：

-- 计算每个指标的熵值
SELECT 
    -SUM(norm_response_time * LOG(norm_response_time)) / LOG(3) AS entropy_response_time,
    -SUM(norm_concurrency_performance * LOG(norm_concurrency_performance)) / LOG(3) AS entropy_concurrency_performance,
    -SUM(norm_scalability * LOG(norm_scalability)) / LOG(3) AS entropy_scalability,
    -SUM(norm_security * LOG(norm_security)) / LOG(3) AS entropy_security,
    -SUM(norm_reliability * LOG(norm_reliability)) / LOG(3) AS entropy_reliability,
    -SUM(norm_maintainability * LOG(norm_maintainability)) / LOG(3) AS entropy_maintainability
FROM (
    SELECT 
        id,
        (response_time - MIN(response_time)) / (MAX(response_time) - MIN(response_time)) AS norm_response_time,
        (concurrency_performance - MIN(concurrency_performance)) / (MAX(concurrency_performance) - MIN(concurrency_performance)) AS norm_concurrency_performance,
        (scalability - MIN(scalability)) / (MAX(scalability) - MIN(scalability)) AS norm_scalability,
        (security - MIN(security)) / (MAX(security) - MIN(security)) AS norm_security,
        (reliability - MIN(reliability)) / (MAX(reliability) - MIN(reliability)) AS norm_reliability,
        (maintainability - MIN(maintainability)) / (MAX(maintainability) - MIN(maintainability)) AS norm_maintainability
    FROM performance_scores
) AS norm_table;

最后，我们可以计算每个指标的权重，例如：

-- 计算每个指标的信息熵权重
SELECT 
    entropy_response_time / SUM(entropy_response_time) AS weight_response_time,
    entropy_concurrency_performance / SUM(entropy_concurrency_performance) AS weight_concurrency_performance,
    entropy_scalability / SUM(entropy_scalability) AS weight_scalability,
    entropy_security / SUM(entropy_security) AS weight_security,
    entropy_reliability / SUM(entropy_reliability) AS weight_reliability,
    entropy_maintainability / SUM(entropy_maintainability) AS weight_maintainability
FROM (
    SELECT 
        -SUM(norm_response_time * LOG(norm_response_time)) / LOG(3) AS entropy_response_time,
        -SUM(norm_concurrency_performance * LOG(norm_concurrency_performance)) / LOG(3) AS entropy_concurrency_performance,
        -SUM(norm_scalability * LOG(norm_scalability)) / LOG(3) AS entropy_scalability,
        -SUM(norm_security * LOG(norm_security)) / LOG(3) AS entropy_security,
        -SUM(norm_reliability * LOG(norm_reliability)) / LOG(3) AS entropy_reliability,
        -SUM(norm_maintainability * LOG(norm_maintainability)) / LOG(3) AS entropy_maintainability
    FROM (
        SELECT 
            id,
            (response_time - MIN(response_time)) / (MAX(response_time) - MIN(response_time)) AS norm_response_time,
            (concurrency_performance - MIN(concurrency_performance)) / (MAX(concurrency_performance) - MIN(concurrency_performance)) AS norm_concurrency_performance,
            (scalability - MIN(scalability)) / (MAX(scalability) - MIN(scalability)) AS norm_scalability,
            (security - MIN(security)) / (MAX(security) - MIN(security)) AS norm_security,
            (reliability - MIN(reliability)) / (MAX(reliability) - MIN(reliability)) AS norm_reliability,
            (maintainability - MIN(maintainability)) / (MAX(maintainability) - MIN(maintainability)) AS norm_maintainability
        FROM performance_scores
    ) AS norm_table
) AS entropy_table;

通过以上 SQL 语句，我们可以得到每个指标的得分，从而进行性能评估。

希望这个案例能够对您有所帮助！