Intelligent computing to solve fifth-order boundary value problem arising in induction motor models

In this study, biologically inspired intelligent computing approached based on artificial neural networks (ANN) models optimized with efficient local search methods like sequential quadratic programming (SQP), interior point technique (IPT) and active set technique (AST) is designed to solve the hig...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Neural computing & applications Ročník 29; číslo 7; s. 449 - 466
Hlavní autoři: Ahmad, Iftikhar, Ahmad, Fayyaz, Raja, Muhammad Asif Zahoor, Ilyas, Hira, Anwar, Nabeela, Azad, Zarqa
Médium: Journal Article
Jazyk:angličtina
Vydáno: London Springer London 01.04.2018
Springer Nature B.V
Témata:
Artificial Intelligence
Artificial neural networks
Boundary value problems
Computation
Computational Biology/Bioinformatics
Computational Science and Engineering
Computer Science
Computer simulation
Data Mining and Knowledge Discovery
Differential equations
Image Processing and Computer Vision
Learning theory
Mathematical models
Neural networks
Original Article
Probability and Statistics in Computer Science
Quadratic programming
Statistical analysis
Transfer functions
Active set technique
Sequential quadratic programming
Interior point technique
Induction motor model
Artificial neural networks
ISSN:0941-0643, 1433-3058
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:In this study, biologically inspired intelligent computing approached based on artificial neural networks (ANN) models optimized with efficient local search methods like sequential quadratic programming (SQP), interior point technique (IPT) and active set technique (AST) is designed to solve the higher order nonlinear boundary value problems arise in studies of induction motor. The mathematical modeling of the problem is formulated in an unsupervised manner with ANNs by using transfer function based on log-sigmoid, and the learning of parameters of ANNs is carried out with SQP, IPT and ASTs. The solutions obtained by proposed methods are compared with the reference state-of-the-art numerical results. Simulation studies show that the proposed methods are useful and effective for solving higher order stiff problem with boundary conditions. The strong motivation of this research work is to find the reliable approximate solution of fifth-order differential equation problems which are validated through strong statistical analysis.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0941-0643
1433-3058
DOI:10.1007/s00521-016-2547-6