Turkish Journal of Computer and Mathematics Education
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Journal

Turkish Journal of Computer and Mathematics Education


Volume
& Issue

Volume 13, Issue 3


Published
on


Pages


DOI

Article

Python-based software for solving clever PDEs


Authors

Basim K. Abbas Affiliation:
Computer Science Department, Collage of Science, Mustansiriyah University, Baghdad-Iraq
, Nadia Mahmood Hussien Affiliation:
Computer Science Department, Collage of Science, Mustansiriyah University, Baghdad-Iraq
, Yasmin Makki Mohialden Affiliation:
Computer Science Department, Collage of Science, Mustansiriyah University, Baghdad-Iraq
and Kawakib Mahmood Hussien Affiliation:
College of Education Ibn Rushd, University of Baghdad, Baghdad-Iraq


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.


Keywords

Python, PyDEns-module, partial differential equations, heat equation, wave equation


Citation

Abbas, B. K., Hussien, N. M., Mohialden, Y. M., & Hussien, K. M. (2022). Python-based software for solving clever pdes. Turkish Journal of Computer and Mathematics Education, 13(3).

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