Python Code Modification: PDE to ODE
Budget: $30 – $250 USD
I'm looking for a proficient Python developer with experience in neural networks and physics-informed models, to modify my existing Python code.
Key Requirements:
- Convert the current code that solves partial differential equations (PDEs) into one that solves first-order ordinary differential equations (ODEs).
- The new implementation should cater to an initial value problem.
- The collocation Runge-Kutta method should be used in a discrete model with discrete time.
- Integrate the Tanh activation function into the neural network as per the PINNs (Physics-Informed Neural Network) methodology.
Ideal Skills:
- Strong knowledge in Python and neural networks.
- Experience with ODEs and PINNs.
- Familiarity with the collocation Runge-Kutta method.
- Understanding of the Tanh activation function and its implementation in neural networks.
Key Requirements:
- Convert the current code that solves partial differential equations (PDEs) into one that solves first-order ordinary differential equations (ODEs).
- The new implementation should cater to an initial value problem.
- The collocation Runge-Kutta method should be used in a discrete model with discrete time.
- Integrate the Tanh activation function into the neural network as per the PINNs (Physics-Informed Neural Network) methodology.
Ideal Skills:
- Strong knowledge in Python and neural networks.
- Experience with ODEs and PINNs.
- Familiarity with the collocation Runge-Kutta method.
- Understanding of the Tanh activation function and its implementation in neural networks.