Computational intelligence methodology for the analysis of RC circuit modelled with nonlinear differential order system

In this study, we solve nonlinear initial value problems arising in circuit analysis by applying bio-inspired computational intelligence technique using feed-forward artificial neural networks (ANNs) optimized with genetic algorithms (GAs), sequential quadratic programming (SQP), and their combined...

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Bibliographic Details
Published in:	Neural computing & applications Vol. 30; no. 6; pp. 1905 - 1924
Main Authors:	Raja, Muhammad Asif Zahoor, Mehmood, Ammara, Niazi, Shahab Ahmad, Shah, Syed Muslim
Format:	Journal Article
Language:	English
Published:	London Springer London 01.09.2018 Springer Nature B.V
Subjects:	Artificial Intelligence Artificial neural networks Boundary value problems Capacitance Circuits Computation Computational Biology/Bioinformatics Computational Science and Engineering Computer Science Data Mining and Knowledge Discovery Energy conservation Error detection Genetic algorithms Image Processing and Computer Vision Intelligence Mathematical models Neural networks Original Article Parameter estimation Performance evaluation Performance measurement Probability and Statistics in Computer Science Quadratic programming RC circuits Runge-Kutta method Statistical analysis Hybrid computing Electric circuits Sequential quadratic programming Artificial neural networks Genetic algorithms
ISSN:	0941-0643, 1433-3058
Online Access:	Get full text
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