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The approaches for the synthesis of an automatic control system using the genetic algorithms are suggested.
This paper presents the development work on an optimisation model for disassembly sequence using the genetic algorithms (GA) approach.
By using the Genetic Algorithms (GAs) optimization method, it is possible to obtain the minimum and maximum solutions which satisfy the inequality.
The Co-Kriging model has been used to get a new optimized cyclone for minimum pressure drop using the genetic algorithms optimization technique.
The methods involve the selection of training datasets for establishing an ANN model by the uniform design method, approximation of the limit state function by the trained ANN model and estimation of the failure probability using the genetic algorithms.
The search for global minimum of a general multidimensional nonlinear function usually involves numerical searching using the genetic algorithms, grid searchers or other computational intensive algorithms.
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The optimization methodology, using the genetic algorithm and the formulation of the problem are detailed.
This paper presents the optimal design of the magnetic microactuator using the genetic algorithm.
The most relevant molecular descriptors were selected using the genetic algorithm as a feature selection tool.
The product unit cost is minimized while the exergy efficiency is maximized using the genetic algorithm.
The optimum structure of ANN has been designed using the genetic algorithm method.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com