Numerical solution of doubly singular nonlinear systems using neural networks-based integrated intelligent computing

In this paper, a bio-inspired computational intelligence technique is presented for solving nonlinear doubly singular system using artificial neural networks (ANNs), genetic algorithms (GAs), sequential quadratic programming (SQP) and their hybrid GA–SQP. The power of ANN models is utilized to devel...

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Vydané v:Neural computing & applications Ročník 31; číslo 3; s. 793 - 812
Hlavní autori: Raja, Muhammad Asif Zahoor, Mehmood, Jabran, Sabir, Zulqurnain, Nasab, A. Kazemi, Manzar, Muhammad Anwaar
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: London Springer London 14.03.2019
Springer Nature B.V
Predmet:
Artificial Intelligence
Artificial neural networks
Comparative studies
Computational Biology/Bioinformatics
Computational Science and Engineering
Computer Science
Data Mining and Knowledge Discovery
Fitness
Genetic algorithms
Image Processing and Computer Vision
Mathematical models
Neural networks
Nonlinear systems
Original Article
Performance indices
Probability and Statistics in Computer Science
Quadratic programming
Sequential quadratic programming
Singular systems
Genetic algorithm
Artificial neural networks
Integrating computing
ISSN:0941-0643, 1433-3058
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Popis
Shrnutí:In this paper, a bio-inspired computational intelligence technique is presented for solving nonlinear doubly singular system using artificial neural networks (ANNs), genetic algorithms (GAs), sequential quadratic programming (SQP) and their hybrid GA–SQP. The power of ANN models is utilized to develop a fitness function for a doubly singular nonlinear system based on approximation theory in the mean square sense. Global search for the parameters of networks is performed with the competency of GAs and later on fine-tuning is conducted through efficient local search by SQP algorithm. The design methodology is evaluated on number of variants for two point doubly singular systems. Comparative studies with standard results validate the correctness of proposed schemes. The consistent correctness of the proposed technique is proven through statistics using different performance indices.
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content type line 14
ISSN:0941-0643
1433-3058
DOI:10.1007/s00521-017-3110-9