Neural Networks and Rules-based Systems used to Find Rational and Scientific Correlations between being Here and Now with Afterlife Conditions
Neural Networks and Rules-based Systems used to Find Rational and
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In this work the new algorithm entitled Reconstruction of Variational Iteration Method (RVIM) is used as an efficient technique in finding the approximate solutions of the linear and nonlinear equations using only few terms of its own iteration. The algorithm can help overcome the difficulty arising in calculating nonlinear intricate terms. Reconstruction of Variational Iteration Method (RVIM) is independent of any small parameters. Besides, it provides us with a simple way to ensure the convergence of series solution, so that we can always get accurate enough approximations. All of these verify the great potential and validity of the RVIM technique in comparison with those of Variational Iteration Method (VIM) for strongly nonlinear problems in science and engineering.
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Dr. Esmail Hesameddini. 2012. \u201cA New Efficient Approach to Analytical Solutions of Parabolic Equations\u201d. Global Journal of Science Frontier Research - F: Mathematics & Decision GJSFR-F Volume 12 (GJSFR Volume 12 Issue F10): .
Crossref Journal DOI 10.17406/GJSFR
Print ISSN 0975-5896
e-ISSN 2249-4626
The methods for personal identification and authentication are no exception.
The methods for personal identification and authentication are no exception.
Total Score: 87
Country: Iran
Subject: Global Journal of Science Frontier Research - F: Mathematics & Decision
Authors: Dr. Esmail Hesameddini, Habibolla Latifizadeh (PhD/Dr. count: 1)
View Count (all-time): 98
Total Views (Real + Logic): 5238
Total Downloads (simulated): 2760
Publish Date: 2012 09, Mon
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Neural Networks and Rules-based Systems used to Find Rational and
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In this work the new algorithm entitled Reconstruction of Variational Iteration Method (RVIM) is used as an efficient technique in finding the approximate solutions of the linear and nonlinear equations using only few terms of its own iteration. The algorithm can help overcome the difficulty arising in calculating nonlinear intricate terms. Reconstruction of Variational Iteration Method (RVIM) is independent of any small parameters. Besides, it provides us with a simple way to ensure the convergence of series solution, so that we can always get accurate enough approximations. All of these verify the great potential and validity of the RVIM technique in comparison with those of Variational Iteration Method (VIM) for strongly nonlinear problems in science and engineering.
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