Loqman, Ibetehaj, Abass, Iraq. (1402). Estimation of parameters of non-linear regression based on PSOGSA algorithm. هنرهای کاربردی, 14(6), 59-71. doi: 10.22075/ijnaa.2022.6981
Ibetehaj Loqman; Iraq T. Abass. "Estimation of parameters of non-linear regression based on PSOGSA algorithm". هنرهای کاربردی, 14, 6, 1402, 59-71. doi: 10.22075/ijnaa.2022.6981
Loqman, Ibetehaj, Abass, Iraq. (1402). 'Estimation of parameters of non-linear regression based on PSOGSA algorithm', هنرهای کاربردی, 14(6), pp. 59-71. doi: 10.22075/ijnaa.2022.6981
Loqman, Ibetehaj, Abass, Iraq. Estimation of parameters of non-linear regression based on PSOGSA algorithm. هنرهای کاربردی, 1402; 14(6): 59-71. doi: 10.22075/ijnaa.2022.6981

Estimation of parameters of non-linear regression based on PSOGSA algorithm

International Journal of Nonlinear Analysis and Applications
مقاله 5، دوره 14، شماره 6، شهریور 2023، صفحه 59-71    اصل مقاله (637.49 K)
نوع مقاله: Research Paper
شناسه دیجیتال (DOI): 10.22075/ijnaa.2022.6981
نویسندگان
Ibetehaj Loqman؛ Iraq T. Abass*
Department of Mathematics, University of Baghdad, Baghdad 00964, Iraq
چکیده
Although computational strategies for taking care of Non-linear Regression Based on Hybrid Algorithms (EPNRHA) to Estimation of Parameters have always been available for years, the further application of Evolutionary Algorithms (EAs) to such difficulties provides a framework for addressing a wide range of Multi-Objective Conflicts (MOPs).  NRPSOGSA is an Estimation of Parameters of Non-linear Regression Gravitational Search Algorithm with Practical Swarm Optimization that involves the synthesis of hegemony by using the hybrid algorithm (PSOGSA) approach is utilized. Whilst Gravitational Search Algorithm with Practical Swarm Optimization Since the leader hiring process uses the Tchebycheff Strategy as a criterion, simplifying the multi-objective problem (MOP) by rewriting it as a set of Tchebycheff Approach, solving these issues at the same time within the GSA context may lead to rapid resolution. Dominance is important in constructing the leader's library because it allows the chosen leaders to encompass fewer dense places, reducing global optimization problems and producing a more diverse approximated Pareto front. 6 non-linear standard functions yielded this result. PSOGSA appears to be more productive than GSA, PSO, and BAT. All of the outcomes were completed. by MATLAB (R2020b).
کلیدواژه‌ها
Estimation Parameter؛ Practice Swarm Algorithm؛ Non-Linear Regression
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