Python-based software for solving clever PDEs

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Basim K. Abbas, Nadia Mahmood Hussien, Yasmin Makki Mohialden, kawakib Mahmood Hussien

Abstract

Several recent investigations have identified a technique for approximating solutions to partial
differential equations (PDEs). However, there was little room for adaptive frameworks that facilitate the
exploration of new concepts. We can compensate by using the PyDEns library in Python. Using the
PyDEns module and the open-source Batch Flow framework, you can solve a variety of partial
differential equations. There are partial differential equations, such as those that describe heat and
waves, and other equations, such as this one. In this article, we explain how to solve differential
equations using neural networks using a new method introduced by Python PyDEns. Partial differential
equations can be solved with this software tool.

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How to Cite
Basim K. Abbas, Nadia Mahmood Hussien, Yasmin Makki Mohialden, kawakib Mahmood Hussien. (2022). Python-based software for solving clever PDEs. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 13(03), 1–6. https://doi.org/10.17762/turcomat.v13i03.12731
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