【Hackathon 7th PPSCI No.8】NO.8 A physics-informed diffusion model for high-fidelity flow field reconstruction 论文复现 #955
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…fidelity flow field reconstruction 论文复现
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luotao1
changed the title
wangguan1995
approved these changes
Sep 19, 2024
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| ### 1.3 意义 | ||
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| > 复现 DPMM 代码，能够使用 DPMM 模型进行训练、验证、导出。 |
| ### 1.2 功能目标 | ||
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| * 复现 DPMM 代码，实现完整的流程，包括：训练、验证、导出。 | ||
| * 保持精度与论文精度一致，相对误差在 ±10% 以内。 |
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数据要盘点清楚：
- 40个，不同的初始边界条件的，视频数据，进行训练
- 测试集4组、训练集36组，按照 9:1划分
- 每组数据320个帧，一共10秒钟时长
- 实际上原数据是1024x1024，进行了下采样，分辨率为256x256
- 每次送进网络的，有3个时间帧的图片（代码）
| 1. 数据预处理 | ||
| 2. 模型构建 | ||
| 3. 超参数设定 | ||
| 4. 验证训练模型的 rel. error |
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注意：
- 误差只有方程部分是相对误差
- 物理场是L2逐点绝对误差，取平均
| ## 6. 可行性分析和排期规划 | ||
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| - 202408：调研 | ||
| - 202409：复现代码并作调整 |
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开发指南（必读）
- 注意文档格式
- 注意必须使用 precommit
参考：https://paddlescience-docs.readthedocs.io/zh-cn/latest/zh/development/
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@AI1LJW 请根据研发导师意见进行修改 |
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好的好的，这段时间有点忙 |
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