caa a22 4500 606158960 CHVBK 20210128100622.0 cr unu---uuuuu 210128e20150101xx s 000 0 eng 10.1007/s00521-014-1676-z doi (NATIONALLICENCE)springer-10.1007/s00521-014-1676-z Design of stochastic solvers based on genetic algorithms for solving nonlinear equations [Elektronische Daten] [Muhammad Raja, Zulqurnain Sabir, Nasir Mehmood, Eman Al-Aidarous, Junaid Khan] 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. The Natural Computing Applications Forum, 2014 Genetic algorithm nationallicence Iterative techniques nationallicence Predictor-corrector method nationallicence Convergence analysis nationallicence Nonlinear equations nationallicence Raja Muhammad Department of Electrical Engineering, COMSATS Institute of Information Technology, Attock Campus, Attock, Pakistan aut Sabir Zulqurnain Department of Mathematics, Preston University Kohat, Islamabad Campus, Islamabad, Pakistan aut Mehmood Nasir Department of Mathematics, Preston University Kohat, Islamabad Campus, Islamabad, Pakistan aut Al-Aidarous Eman Department of Mathematics, King Abdulaziz University, 21589, Jeddah, Kingdom of Saudi Arabia aut Khan Junaid Hamdard Institute of Information Technology, Hamdard University, Islamabad Campus, Islamabad, Pakistan aut Neural Computing and Applications Springer London 26/1(2015-01-01), 1-23 0941-0643 26:1<1 2015 26 521 https://doi.org/10.1007/s00521-014-1676-z text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00521-014-1676-z text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Raja Muhammad Department of Electrical Engineering, COMSATS Institute of Information Technology, Attock Campus, Attock, Pakistan aut NATIONALLICENCE 700 1- Sabir Zulqurnain Department of Mathematics, Preston University Kohat, Islamabad Campus, Islamabad, Pakistan aut NATIONALLICENCE 700 1- Mehmood Nasir Department of Mathematics, Preston University Kohat, Islamabad Campus, Islamabad, Pakistan aut NATIONALLICENCE 700 1- Al-Aidarous Eman Department of Mathematics, King Abdulaziz University, 21589, Jeddah, Kingdom of Saudi Arabia aut NATIONALLICENCE 700 1- Khan Junaid Hamdard Institute of Information Technology, Hamdard University, Islamabad Campus, Islamabad, Pakistan aut NATIONALLICENCE 773 0- Neural Computing and Applications Springer London 26/1(2015-01-01), 1-23 0941-0643 26:1<1 2015 26 521