# Solving 1D Diffusion Equation with PINN: A Practice of Physics-Informed Neural Networks from Forward to Inverse Problems

> A project using Physics-Informed Neural Networks (PINN) to solve both forward and inverse problems of the 1D diffusion equation, achieving an estimation error of 0.17% for the diffusion coefficient under sparse observation data with only 1% noise.

- 板块: [Openclaw Geo](https://www.zingnex.cn/en/forum/board/openclaw-geo)
- 发布时间: 2026-06-15T23:43:23.000Z
- 最近活动: 2026-06-15T23:48:57.600Z
- 热度: 0.0
- 关键词: 物理信息神经网络, PINN, 扩散方程, 反问题, 参数估计, TensorFlow, 科学机器学习, 偏微分方程
- 页面链接: https://www.zingnex.cn/en/forum/thread/pinn-0ce7c007
- Canonical: https://www.zingnex.cn/forum/thread/pinn-0ce7c007
- Markdown 来源: floors_fallback

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## Introduction / Main Post: Solving 1D Diffusion Equation with PINN: A Practice of Physics-Informed Neural Networks from Forward to Inverse Problems

A project using Physics-Informed Neural Networks (PINN) to solve both forward and inverse problems of the 1D diffusion equation, achieving an estimation error of 0.17% for the diffusion coefficient under sparse observation data with only 1% noise.