2013
DOI: 10.1080/10407782.2013.733179
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Simultaneous Retrieval of Parameters in a Transient Conduction-Radiation Problem Using a Differential Evolution Algorithm

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Cited by 34 publications
(9 citation statements)
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“…In the recent decades, many swarm intelligence algorithms, including differential evolution [35,36], genetic algorithm [37,38], and PSO [39][40][41], have been analyzed and applied in various industrial fields. These algorithms can effectively overcome the drawbacks and limitations of the aforementioned conventional gradient-based techniques.…”
Section: Methodsmentioning
confidence: 99%
“…In the recent decades, many swarm intelligence algorithms, including differential evolution [35,36], genetic algorithm [37,38], and PSO [39][40][41], have been analyzed and applied in various industrial fields. These algorithms can effectively overcome the drawbacks and limitations of the aforementioned conventional gradient-based techniques.…”
Section: Methodsmentioning
confidence: 99%
“…More recently, some new intelligent optimization techniques have been proposed to solve the coupled conductionradiation problems to look for improvements besides GA and PSO. Chopade et al [22] investigated the transient inverse problem of coupled conduction-radiation heat transfer using Differential Evolution algorithm. A new Homogenous Continuous ACO algorithm was developed by our group to retrieve the thermophysical parameters of participating medium in the problem of coupled conduction-radiation [23].…”
Section: Introductionmentioning
confidence: 99%
“…[32] It is observed that compared to other evolutionary optimization algorithms, the DE [33] possesses few advantages such as robustness, fast convergence, compact structure, ease of implementation and its efficacy for optimising nonlinear search domains. [34][35][36][37] For combining the benefits of deterministic methods and stochastic methods, recently the usage of hybrid optimization methods is becoming popular. [38] Based on the above, the focus of the present work is to predict parameters such as the thermal conductivity of the fin material, the coefficient of its variation and the surface heat transfer coefficient for satisfying a prescribed temperature in a hyperbolic annular fin with temperature-dependent thermal conductivity.…”
Section: Introductionmentioning
confidence: 99%