Artificial Neural Networks for Engineers and Scientists: Solving Ordinary Differential Equations

✍ Scribed by S. Chakraverty, Susmita Mall

• Publisher: CRC Press;Chakraverty, Snehashish, CRC Pr I Llc, Mall, Susmita
• Year: 2017
• Tongue: English
• Leaves: 169
• Edition: 1
• Category: Library

✦ Synopsis

Differential equations play a vital role in the fields of engineering and science. Problems in engineering and science can be modeled using ordinary or partial differential equations. Analytical solutions of differential equations may not be obtained easily, so numerical methods have been developed to handle them. Machine intelligence methods, such as Artificial Neural Networks (ANN), are being used to solve differential equations, and these methods are presented in Artificial Neural Networks for Engineers and Scientists: Solving Ordinary Differential Equations. This book shows how computation of differential equation becomes faster once the ANN model is properly developed and applied

✦ Table of Contents

Content: Preliminaries of Artificial Neural Networks (ANN). Preliminaries of Ordinary Differential Equations (ODEs). Multi layer Neural Networks. Regression based ANN. Single layer Functional Link Artificial Neural Networks (FLANN). Single layer Functional Link Artificial Neural Network (FLANN) with Regression-based Weights. Lane-Emden Equations through Artificial Neural Networks. Emden-Fowler Equations through Artificial Neural Networks. Duffing Oscillator Equations through Artificial Neural Networks. Vanderpol Duffing Oscillator Equations through Artificial Neural Networks.