2020
DOI: 10.1016/j.aej.2019.12.001
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A study of changes in temperature profile of porous fin model using cuckoo search algorithm

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Cited by 87 publications
(33 citation statements)
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References 53 publications
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“…In the future, one may explore, investigate, or exploit the stochastic numerical computing approaches based on the artificial intelligence paradigm [37][38][39][40][41][42][43][44] for alternate, accurate, robust, and stable solutions, not only for the given biological fluidic model involving nano-materials, but also for other stiff nonlinear systems, which are still a challenge for traditional/classical numerical methods.…”
Section: Discussionmentioning
confidence: 99%
“…In the future, one may explore, investigate, or exploit the stochastic numerical computing approaches based on the artificial intelligence paradigm [37][38][39][40][41][42][43][44] for alternate, accurate, robust, and stable solutions, not only for the given biological fluidic model involving nano-materials, but also for other stiff nonlinear systems, which are still a challenge for traditional/classical numerical methods.…”
Section: Discussionmentioning
confidence: 99%
“…(6) via Meyer wavelet neural networks (MWNN) optimized with global search efficacy of genetic algorithms (GAs) and sequential quadratic programming (SQP), i.e., MWNN-GASQP. The solvers based on meta-heuristic intelligent computing have been extensively applied for the analysis of linear/nonlinear, singular/non-singular systems using neural networks optimized with evolutionary/swarming-based computing schemes (Lodhi 2019;Raja et al 2017a;Bukhari 2020;Waseem 2020;Ahmad 2020Ahmad ,2019. Some recent applications of the evolutionary/swarming-based numerical computing are PainlevĂŠ equation-based models in random matrix theory (Raja et al 2018a), nonlinear prey-predator models (Umar 2019), Bagley-Torvik systems in fluid mechanics.…”
Section: Problem Statement and Related Workmentioning
confidence: 99%
“…f (∞) = S ic , T = 0, X > 0, (38) transforming the boundary condition Eq (38) into variational condition, we have…”
Section: B Homogenous Porous Mediummentioning
confidence: 99%
“…The optimal design of heat fins is proposed in [36]. A study of temperature distribution in heat fins is carried out by using a hybrid of the Cuckoo Search (CS) algorithm and Artificial Neural Network architecture [37], [38]. Neuro-fuzzy modeling is used to predict the summer precipitation in targeted metrological sites [39].…”
mentioning
confidence: 99%