An Application of Evolutionary Computational Technique to Non-Linear Singular System arising in Polytrophic and Isothermal sphere

1
Junaid Ali Khan
Junaid Ali Khan
2
Muhammad Asif Zahoor Raja
Muhammad Asif Zahoor Raja
3
Ijaz Mansoor Qureshi
Ijaz Mansoor Qureshi
1 International Islamic University Islamabad, Pakistan

Send Message

To: Author

GJRE Volume 12 Issue I1

Article Fingerprint

ReserarchID

0J34P

An Application of Evolutionary Computational Technique to Non-Linear Singular System arising in Polytrophic and Isothermal sphere Banner
  • English
  • Afrikaans
  • Albanian
  • Amharic
  • Arabic
  • Armenian
  • Azerbaijani
  • Basque
  • Belarusian
  • Bengali
  • Bosnian
  • Bulgarian
  • Catalan
  • Cebuano
  • Chichewa
  • Chinese (Simplified)
  • Chinese (Traditional)
  • Corsican
  • Croatian
  • Czech
  • Danish
  • Dutch
  • Esperanto
  • Estonian
  • Filipino
  • Finnish
  • French
  • Frisian
  • Galician
  • Georgian
  • German
  • Greek
  • Gujarati
  • Haitian Creole
  • Hausa
  • Hawaiian
  • Hebrew
  • Hindi
  • Hmong
  • Hungarian
  • Icelandic
  • Igbo
  • Indonesian
  • Irish
  • Italian
  • Japanese
  • Javanese
  • Kannada
  • Kazakh
  • Khmer
  • Korean
  • Kurdish (Kurmanji)
  • Kyrgyz
  • Lao
  • Latin
  • Latvian
  • Lithuanian
  • Luxembourgish
  • Macedonian
  • Malagasy
  • Malay
  • Malayalam
  • Maltese
  • Maori
  • Marathi
  • Mongolian
  • Myanmar (Burmese)
  • Nepali
  • Norwegian
  • Pashto
  • Persian
  • Polish
  • Portuguese
  • Punjabi
  • Romanian
  • Russian
  • Samoan
  • Scots Gaelic
  • Serbian
  • Sesotho
  • Shona
  • Sindhi
  • Sinhala
  • Slovak
  • Slovenian
  • Somali
  • Spanish
  • Sundanese
  • Swahili
  • Swedish
  • Tajik
  • Tamil
  • Telugu
  • Thai
  • Turkish
  • Ukrainian
  • Urdu
  • Uzbek
  • Vietnamese
  • Welsh
  • Xhosa
  • Yiddish
  • Yoruba
  • Zulu

The paper presents a method to solve singular non-linear system representing polytrophic and isothermal sphere using neural network optimized by evolutionary computational approach. A trial solution of the system is written as a feed-forward neural network containing adaptive parameters (weights and biases). We prepare a fitness evaluation function defining unsupervised error. The optimization of the error defines the accuracy in the model that is highly stochastic in nature. Genetic algorithm is exploited as a tool for global convergence and active set algorithm as a rapid local search. The given scheme is tested on the model with polytrophic index 5=λ . A comparative study is made with exact and optimal Homtopy asymptotic method. The stability and reliability of the proposed scheme is investigated by a comprehensive statistical analysis. The proposed results are found to be in good agreement with exact solution as well as numerical solvers.

27 Cites in Articles

References

  1. C Saloma (1993). Computational complexity and observation of physical signals.
  2. C Monterola,C Saloma (1998). Characterizing the dynamics of constrained physical systems with unsupervised neural network.
  3. J Gao,B Liu (2005). Fuzzy multilevel programming with a hybrid intelligent algorithm.
  4. L Wang (2005). Tagebuch.
  5. David Fogel (2000). Evolutionary Computation.
  6. D Fogel,A Ghozi (1997). Schema processing under proportional selection in the presence of random effects.
  7. J Koza (1992). Genetic Programming.
  8. H-P Schwefel (1995). Evolution and optimum seeking.
  9. T Back Evolutionary algorithms in theory and practice.
  10. D Fogel (2006). Evolutionary Computation: Towar a new philosophy of machine intelligence.
  11. T Yokota,M Gen,Y Li (1996). Genetic algorithm for non-linear mixed integer programming problems and it's application.
  12. K Lee,M El-Sharkawi (2008). Modern Huristic Optimization Techniques: Theory and application to power systems.
  13. A Mantawy,Y Abdel-Magid,S Selim (1999). Integrating genetic algorithms, tabu search, and simulated annealing for the unit commitment problem.
  14. L Aarts,P Veer Neural Network Method for solving the partial Differential Equations.
  15. Ioannis Tsoulos,Dimitris Gavrilis,Euripidis Glavas (2009). Solving differential equations with constructed neural networks.
  16. Junaid Khan,Raja Zahoor,Ijaz Qureshi (2009). Swarm Intelligence for the Solution of Problems in Differential Equations.
  17. Janez Brest,Sao Greiner,Borko Boskovic,Marjan Mernik,Viljem Zumer (2006). Self-Adapting Control Parameters in Differential Evolution: A Comparative Study on Numerical Benchmark Problems.
  18. M Raja,J Khan,I Qureshi (2011). A new Stochastic Approach for Solution of Riccati Differential Equation of Fractional Order.
  19. D Rarisi (2003). Solving differential equations with unsupervised neural networks.
  20. J Khan,M Raja,I Qureshi (2011). Stochastic Computational Approach for Complex Non-linear Ordinary Differential Equations.
  21. S Iqbal,A Javed (2011). Application of optimal homotopy asymptotic method for the analytic solution of singular Lane–Emden type equation.
  22. Nicolae Herisanu,Vasile Marinca (2008). An effective analytical approach to nonlinear free vibration of elastically actuated microtubes.
  23. Nicolae Vasile Marinca,Herisanu (2008). Application of optimal homotopy asymptotic method for solving nonlinear equations arising in heat transfer.
  24. Nicolae Vasile Marinca,Constantin Herisanu,Bogdan Bota,Marinca (2009). An optimal homotopy asymptotic method applied to the steady flow of a fourth grade fluid past a porous plate.
  25. Nicolae Vasile Marinca,Iacob Herisanu,Nemes (2008). optimal homotopy asymptotic method with application to thin film flow.
  26. S Iqbal,M Idrees,A Siddiqui,A Ansari (2010). Some solutions of the linear and nonlinear Klein-Gordon equations using the optimal homotopy asymptotic method.
  27. L Qin,M Yang (2007). Moving mass attitude law based on neural networks.

Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

Junaid Ali Khan. 2012. \u201cAn Application of Evolutionary Computational Technique to Non-Linear Singular System arising in Polytrophic and Isothermal sphere\u201d. Global Journal of Research in Engineering - I: Numerical Methods GJRE-I Volume 12 (GJRE Volume 12 Issue I1): .

Download Citation

Journal Specifications

Crossref Journal DOI 10.17406/gjre

Print ISSN 0975-5861

e-ISSN 2249-4596

Classification
Not Found
Version of record

v1.2

Issue date

March 14, 2012

Language

English

Experiance in AR

The methods for personal identification and authentication are no exception.

Read in 3D

The methods for personal identification and authentication are no exception.

Article Matrices
Total Views: 5428
Total Downloads: 2703
2026 Trends
Research Identity (RIN)
Related Research

Published Article

The paper presents a method to solve singular non-linear system representing polytrophic and isothermal sphere using neural network optimized by evolutionary computational approach. A trial solution of the system is written as a feed-forward neural network containing adaptive parameters (weights and biases). We prepare a fitness evaluation function defining unsupervised error. The optimization of the error defines the accuracy in the model that is highly stochastic in nature. Genetic algorithm is exploited as a tool for global convergence and active set algorithm as a rapid local search. The given scheme is tested on the model with polytrophic index 5=λ . A comparative study is made with exact and optimal Homtopy asymptotic method. The stability and reliability of the proposed scheme is investigated by a comprehensive statistical analysis. The proposed results are found to be in good agreement with exact solution as well as numerical solvers.

Our website is actively being updated, and changes may occur frequently. Please clear your browser cache if needed. For feedback or error reporting, please email [email protected]
×

This Page is Under Development

We are currently updating this article page for a better experience.

Request Access

Please fill out the form below to request access to this research paper. Your request will be reviewed by the editorial or author team.
X

Quote and Order Details

Contact Person

Invoice Address

Notes or Comments

This is the heading

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Ut elit tellus, luctus nec ullamcorper mattis, pulvinar dapibus leo.

High-quality academic research articles on global topics and journals.

An Application of Evolutionary Computational Technique to Non-Linear Singular System arising in Polytrophic and Isothermal sphere

Junaid Ali Khan
Junaid Ali Khan International Islamic University Islamabad, Pakistan
Muhammad Asif Zahoor Raja
Muhammad Asif Zahoor Raja
Ijaz Mansoor Qureshi
Ijaz Mansoor Qureshi

Research Journals