Open AccessEfficient Design of Neural Networks for Solving Third Order Partial Differential Equations
Author(s) -
L. N. M. Tawfiq,
Muna H. Ali
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1530/1/012067
Subject(s) - artificial neural network , partial differential equation , computer science , order (exchange) , function (biology) , mathematical optimization , differential (mechanical device) , third order , differential equation , mathematics , artificial intelligence , engineering , mathematical analysis , finance , evolutionary biology , economics , biology , aerospace engineering , philosophy , theology
The aim of the research is design efficient neural networks to solve important type of partial differential equations represent many important models. The efficiency of design based on chooses a suitable activation function, suitable training algorithms with study how to increase the speed of this algorithm. Then we used suggested design to solve third order PDEs.