2022
DOI: 10.1080/17455030.2022.2094028
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Design of artificial neural networks optimized through genetic algorithms and sequential quadratic programming for tuberculosis model

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Cited by 5 publications
(3 citation statements)
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“…GAs is a well‐known global solver used in the current research for optimization of MHD Prandtl–Eyring fluid flow problem through the most appropriate selection of generation, mutation, crossover, population and elitism. The applications [59, 67–69] of GAs proves its effectiveness.…”
Section: Problem Methodologymentioning
confidence: 99%
See 1 more Smart Citation
“…GAs is a well‐known global solver used in the current research for optimization of MHD Prandtl–Eyring fluid flow problem through the most appropriate selection of generation, mutation, crossover, population and elitism. The applications [59, 67–69] of GAs proves its effectiveness.…”
Section: Problem Methodologymentioning
confidence: 99%
“…ANNs-based stochastic numerical techniques are used quite successfully to solve nonlinear systems of ODEs involved in real-world problems to a large extent for rapid convergence in the fields of biomedical, engineering, welding, finance, material science, medicine and geology. Some recent applications of ANNs in the fields of applied science are including the SEIR Ebola model [48], COVID-19 [49,50], squeezing flow paradigm [51], delay model [52], computer virus handling [53], spline model [54], corneal model [55], Lassa fever model [56], Falkner-Skan model [57], VPSA model [58], tuberculosis model [59], hydrogen purification model [60], nanofluids [61], nanoparticles [62], hybrid nanofluids [63], and induction motor [64]. The above-mentioned literature interprets the successful application of ANNs but as per the author's knowledge, ANNs-IMQ algorithm is never applied to scrutinize the MHD Prandtl-Eyring fluid flow model with radiation and convecting heating impacts over a stretched sheet.…”
Section: Introductionmentioning
confidence: 99%
“…Multi-objective GA and an artificial neural network model produce global objective function results. Process variable optimization improves quality and reduces machining time and expense [8].…”
Section: Introductionmentioning
confidence: 99%