Paper Title:
An Optimizing Design Approach for the Fiber Manufacturing Based on the Immune Genetic Algorithm-Optimized Neural Network
  Abstract

A novel neural network-based approach with immune genetic algorithm is proposed to conduct the optimizing design for the industrial filament manufacturing system. A new model is proposed in this paper to acquire better filament quality during such process. The proposed model was a combination of two components, namely, a traditional neural network which is used to simulate and an immune genetic algorithm-based part which is to improve the performance of the neural network component. Simulation results demonstrate that the proposed method can efficiently demonstrate the spinning process of filament and conduct the prediction of the filament quality with the production parameters as input data. Meanwhile, the proposed method enjoys faster speed and more precise accuracy, compared with traditional methods.

  Info
Periodical
Edited by
Yanwen Wu
Pages
19-24
DOI
10.4028/www.scientific.net/AMR.267.19
Citation
H. Z. Zhu, Y. S. Ding, X. Liang, K. R. Hao, H. P. Wang, "An Optimizing Design Approach for the Fiber Manufacturing Based on the Immune Genetic Algorithm-Optimized Neural Network", Advanced Materials Research, Vol. 267, pp. 19-24, 2011
Online since
June 2011
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