2022
DOI: 10.1007/s10845-022-01935-y
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Nature inspired algorithms for the solution of inverse heat transfer problems applied to distinct unsteady heat flux orientations in cylindrical castings

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Cited by 2 publications
(3 citation statements)
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“…It is a type of opposition-based learning strategy that effectively improves the search range of algorithms and prevents them from falling into local optima too early. This strategy is described by the following equation: S t+1 = rand(min((u j + l j ) * γ, u j + l j − S t ), max((u j + l j ) * γ, u j + l j − S t )), (25) where, γ represents random numbers uniformly distributed on [0, 1]; u j , l j respectively represent the upper and lower bounds of the j dimension of the squirrel search interval; S t represents the position of the t th generation of trees.…”
Section: Random Opposition-based Learning Strategymentioning
confidence: 99%
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“…It is a type of opposition-based learning strategy that effectively improves the search range of algorithms and prevents them from falling into local optima too early. This strategy is described by the following equation: S t+1 = rand(min((u j + l j ) * γ, u j + l j − S t ), max((u j + l j ) * γ, u j + l j − S t )), (25) where, γ represents random numbers uniformly distributed on [0, 1]; u j , l j respectively represent the upper and lower bounds of the j dimension of the squirrel search interval; S t represents the position of the t th generation of trees.…”
Section: Random Opposition-based Learning Strategymentioning
confidence: 99%
“…Since the intelligent algorithms have advantages in solving complex optimization problems, a great deal of research works have been done to solve the inverse problems of partial differential equations. For example, in [25], genetic algorithm (GA), evolutionary strategy (ES), artificial immune system (AIS) and particle swarm algorithm (PSO) have been integrated to solve the inverse heat transfer problem. Silva-Santos, et al [26] applied artificial immune system algorithm to the solution of an inverse heat transfer problem in unsteady inward solidification.…”
Section: Introductionmentioning
confidence: 99%
“…In addition, this approach ignores students' autonomous learning ability, and their ability to solve problems becomes relatively weak. Traditional teaching methods can no longer keep up with the rapid development of modern society, so the use of multimedia computer technology and other equipment for teaching has become an inevitable trend in the development of modern teaching technology (da Silva-Santos et al, 2023). The application of multimedia technology in music teaching in colleges and universities can first make the teaching more vivid with pictures and texts, and make the abstract image of music concrete, visualized, and intuitive, so that students can integrate into the music situation to the maximum extent and feel the music.…”
Section: Introductionmentioning
confidence: 99%