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Title of Journal: Neural Comput Applic

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Abbravation: Neural Computing and Applications

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Publisher

Springer London

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DOI

10.1016/0016-3287(79)90100-9

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ISSN

1433-3058

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Design of stochastic solvers based on genetic algo

Authors: Muhammad Asif Zahoor Raja Zulqurnain Sabir Nasir Mehmood Eman S AlAidarous Junaid Ali Khan
Publish Date: 2014/07/30
Volume: 26, Issue: 1, Pages: 1-23
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Abstract

In the present study a novel intelligent computing approach is developed for solving nonlinear equations using evolutionary computational technique mainly based on variants of genetic algorithms GA The mathematical model of the equation is formulated by defining an error function Optimization of fitness function is carried out with the competency of GA used as a tool for viable global search methodology Comprehensive numerical experimentation has been performed on number of benchmark nonlinear algebraic and transcendental equations to validate the accuracy convergence and robustness of the designed scheme Comparative studies have also been made with available standard solution to establish the correctness of the proposed scheme Reliability and effectiveness of the design approaches are validated based on results of statistical parameters

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