 2569718930@qq.com
|
be549daf50
|
fix: use multi-model peak window for gaussian probability
|
2026-05-28 10:03:29 +08:00 |
|
|
2569718930@qq.com
|
fb4a9d7e09
|
fix: align gaussian probability with local forecast date
|
2026-05-28 09:44:42 +08:00 |
|
|
2569718930@qq.com
|
8609376c59
|
feat: add versioned DEB bias backtesting
|
2026-05-27 21:40:26 +08:00 |
|
|
2569718930@qq.com
|
0e4e7aebb2
|
项目体检修复：删除破损的 LGBM 导入、8个死测试、2个死脚本、移除 pytz/lightgbm 依赖
|
2026-05-18 22:43:34 +08:00 |
|
|
2569718930@qq.com
|
0e0aad3171
|
删除 LGBM 全部代码和模型文件，EMOS 简化为纯 legacy 高斯分桶模式
|
2026-05-18 22:05:55 +08:00 |
|
|
2569718930@qq.com
|
974b55e34f
|
Add full probability distributions to dashboard
|
2026-04-22 01:43:13 +08:00 |
|
|
2569718930@qq.com
|
0cc4f4f0d3
|
Add LightGBM daily high forecasting pipeline
|
2026-03-29 23:29:17 +08:00 |
|
|
2569718930@qq.com
|
2b0e6a6f67
|
Add Wunderground as Shenzhen settlement source
|
2026-03-25 17:00:36 +08:00 |
|
|
2569718930@qq.com
|
ace9c71743
|
Align Taipei settlement to NOAA RCTP across web and extension
|
2026-03-23 14:39:41 +08:00 |
|
|
2569718930@qq.com
|
c795d90993
|
Sync dynamic commentary across bot and dashboard
|
2026-03-21 18:54:23 +08:00 |
|
|
2569718930@qq.com
|
3196552c78
|
Archive probability snapshots and wire them into training
|
2026-03-20 21:30:52 +08:00 |
|
|
2569718930@qq.com
|
1c84893bed
|
Add CI and shadow calibration reporting
|
2026-03-20 20:59:30 +08:00 |
|
|
2569718930@qq.com
|
e4cc5b4263
|
feat: Add initial web dashboard and centralize weather trend analysis logic into a shared engine.
|
2026-03-20 18:16:21 +08:00 |
|
|
2569718930@qq.com
|
dbf10253a8
|
feat: Implement multi-source weather data collection with caching, rate limiting, and disk persistence.
|
2026-03-20 13:35:34 +08:00 |
|
|
2569718930@qq.com
|
54544e40b9
|
feat: Implement core data models, backend services for weather and market data, and initial dashboard components.
|
2026-03-17 13:21:14 +08:00 |
|
|
2569718930@qq.com
|
f4fea03f35
|
feat: Implement new bot architecture including handlers, services, analysis modules, and comprehensive tests.
|
2026-03-12 11:44:52 +08:00 |
|
|
2569718930@qq.com
|
0877efe0c3
|
feat: Introduce new ai_analyzer and trend_engine modules for comprehensive weather trend and AI analysis.
|
2026-03-12 10:26:28 +08:00 |
|
|
2569718930@qq.com
|
1060945d08
|
feat: Implement Dynamic Ensemble Blending (DEB) algorithm with historical data management, dynamic weight calculation, and accuracy tracking.
|
2026-03-12 02:32:10 +08:00 |
|
|
2569718930@qq.com
|
1958b2764b
|
feat: Implement core PolyWeather application with city weather query service, trend analysis, data collection, and dashboard UI.
|
2026-03-11 10:49:35 +08:00 |
|
|
2569718930@qq.com
|
2b681513ab
|
fix(trend-engine): fallback to non-ensemble probability computation when OM drops to keep UI alive
|
2026-03-11 05:07:41 +08:00 |
|
|
2569718930@qq.com
|
c5010a8b97
|
fix: safely fallback to metric unit per city instead of overwriting F to C randomly; allow trend engine to run even if Open-Meteo drops
|
2026-03-11 04:57:58 +08:00 |
|
|
2569718930@qq.com
|
aab4477ab3
|
feat: Implement the PolyWeather dashboard including frontend components, data collection, analysis, and API endpoints.
|
2026-03-10 04:45:40 +08:00 |
|
|
2569718930@qq.com
|
a1416d1324
|
feat: introduce PolyWeather application with an interactive map, detailed city weather, trend analysis, and a supporting API.
|
2026-03-05 04:28:35 +08:00 |
|
|
2569718930@qq.com
|
9e5fc418de
|
feat: Extract weather trend analysis into a new shared module and add initial web application and data collection components.
|
2026-03-04 19:47:19 +08:00 |
|
|
2569718930@qq.com
|
7329dd728e
|
refactor: extract trend_engine, unify probability engine across bot and web, add unit tests
|
2026-03-04 02:52:31 +08:00 |
|