趋势分析增加参数

jjt-biz/src/main/java/com/jjt/calc/vo/StopVO.java

@@ -26,10 +26,18 @@ public class StopVO {
     private Double slope;
     @ApiModelProperty("标准差")
     private Double stdDev;
+    @ApiModelProperty("平均值")
+    private Double mean;
+    @ApiModelProperty("变异系数")
+    private Double coefficientOfVariation;
+    @ApiModelProperty("斜率阈值")
+    private Double slopeThreshold;
+    @ApiModelProperty("变异系数阈值")
+    private Double cvThreshold;
     @ApiModelProperty("分析结果")
     private String result;
     @ApiModelProperty("停机详情")
     List<StopDetail> list;
     @ApiModelProperty("附加信息")
     private Map<String, Object> additionalInfo;
-}
+}

jjt-biz/src/main/java/com/jjt/utils/TrendAnalysis.java

@@ -41,9 +41,18 @@ public class TrendAnalysis {
     public static void analysisDetail(StopVO vo, List<Integer> times) {
         // 计算线性回归斜率
         double slope = calculateSlope(times);
-
         // 计算标准差
         double stdDev = calculateStandardDeviation(times);
+        // 计算平均值
+        double mean = times.stream().mapToInt(Integer::intValue).average().orElse(0);
+        // 计算变异系数
+        double coefficientOfVariation = mean != 0 ? stdDev / mean : 0;
+
+        // 定义阈值
+        // 5%的平均值作为斜率阈值
+        double slopeThreshold = Math.abs(mean * 0.05);
+        // 变异系数阈值
+        double cvThreshold = 0.1;
 
         // 判断趋势类型
         String trend = determineTrend(slope, stdDev, times);
@@ -51,8 +60,15 @@ public class TrendAnalysis {
         vo.setStdDev(stdDev);
         vo.setResult(trend);
         vo.setDataNum(times.size());
+        // 添加平均值和变异系数到vo中
+        vo.setMean(mean);
+        vo.setCoefficientOfVariation(coefficientOfVariation);
+        // 添加阈值到vo中
+        vo.setSlopeThreshold(slopeThreshold);
+        vo.setCvThreshold(cvThreshold);
     }
 
+
     /**
      * 批量趋势分析并返回统计结果
      *
@@ -181,4 +197,4 @@ public class TrendAnalysis {
             }
         }
     }
-}
+}