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Optimisation of the Fibre-to-Yarn Process Using Genetic Algorithms.
- 출판일1998.08
- 저자
- 서지사항
- 등록일 2016.11.02
- 조회수 222
Researchers simulated and optimized the fiber to yarn production process using a backpropagation neural network combined with a genetic algorithm. The neural network models the process, using the machine settings and fiber quality parameters as input and the yarn tenacity and elongation as output. The genetic algorithm then calculates the input parameters required for obtaining high quality yarn. The resulting yarn, based upon the optimization of available fiber qualities toward the Pareto front, closely matches the yarn characteristics predicted by the simulation. 19 refs.
