Data Analysis
时间序列异常检测器
上传 CSV 或 JSON 时间序列数据，基于 Z-Score 和 IQR 检测异常点，并输出带图表的报告
html· HTML 结果打开工具
快速开始
用三种语言从你的代码中调用此工具。
cURL
# 1) Request a presigned URL → returns { uploadUrl, storageKey }
curl -X POST 'https://api.elysiatools.com/api/upload/presign/time-series-anomaly-detector' \
-H 'Content-Type: application/json' \
-d '{"filename":"dataFile.ext","contentType":"application/octet-stream","size":12345}'
# 2) PUT the file bytes directly to the presigned uploadUrl
curl -X PUT '<presigned uploadUrl>' \
--data-binary @/path/to/file.ext
# 3) Call the tool, passing the returned storageKey for each file field
curl -X POST 'https://api.elysiatools.com/zh/api/tools/time-series-anomaly-detector' \
-F 'rawInput=timestamp,value
2026-03-01,110
2026-03-02,112
2026-03-03,109
2026-03-04,315
2026-03-05,111' \
-F 'dataFile=uploads/2026/01/01/your-tool-1700000000000-abc123.ext' \
-F 'timestampColumn=timestamp' \
-F 'valueColumn=value' \
-F 'detectionMethod=both' \
-F 'zScoreThreshold=2.5' \
-F 'seasonalityWindow=0'