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- W2965307997 abstract "Location layout of aircraft assembly is an important factor affecting product quality. Most of the existing re-searches use the combination of finite element analysis and intelligent algorithm to optimize the location layout, which are limited by numerical simulation accuracy and the selection and improvement of intelligent algorithms. At present, the analysis and decision-making technology based on field data is gradually applied in aircraft manufacturing. Based on the perception data of intelligent assembly unit of aircraft parts, a regression model of multi-input and multi-output support vector machine with Gauss kernel function as radial basis function is established, and the hyperparameters of the model are optimized by hybrid particle swarm optimization genetic algorithm (PSO-GA). GA-MSVR, PSO-MSVR and PSOGA-MSVR model are constructed respectively, and their results show that PSOGA-MSVR model has the best performance. Finally, the design of the aircraft wing location layout is taken as an example to verify the effectiveness of the method." @default.
- W2965307997 created "2019-08-13" @default.
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- W2965307997 date "2020-05-01" @default.
- W2965307997 modified "2023-09-27" @default.
- W2965307997 title "Location layout design of aircraft parts assembly based on MSVR" @default.
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- W2965307997 doi "https://doi.org/10.1016/j.cja.2019.07.020" @default.
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