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Erschienen in: Neural Computing and Applications 9/2021

21.03.2021 | S.I. : SPIoT 2020

RETRACTED ARTICLE: Product modeling design based on genetic algorithm and BP neural network

verfasst von: Jia-Xuan Han, Min-Yuan Ma, Kun Wang

Erschienen in: Neural Computing and Applications | Ausgabe 9/2021

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Abstract

At present, the rapid development of industrial products still lacks reliable theoretical support in terms of styling design. In order to provide a set of effective reference basis for designing a better product appearance plan, this paper takes the shape design of drones as an example. The optimization feature of genetic algorithm optimizes the BP neural network to construct a hybrid GA–BP model, so as to efficiently evaluate and screen out scientific design schemes. By adding 13 of the 16 selected product design schemes to the hybrid GA–BP evaluation system, we perform training to obtain simulated and actual values, and finally, the remaining three design schemes are used for verification. Our results show that the relative errors of the two sets of data verification are 3.4%, 1.9% and 3.1%, respectively. In theory, such accuracy is very high, which basically reflects that the evaluation system of hybrid GA–BP product modeling design enables the design plan to be evaluated quickly, conveniently, effectively and scientifically.

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Metadaten
Titel
RETRACTED ARTICLE: Product modeling design based on genetic algorithm and BP neural network
verfasst von
Jia-Xuan Han
Min-Yuan Ma
Kun Wang
Publikationsdatum
21.03.2021
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 9/2021
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-020-05604-0

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