Please use this identifier to cite or link to this item: http://buratest.brunel.ac.uk/handle/2438/8485
Title: Bidirectional optimization of the melting spinning process
Authors: Liang, X
Ding, Y
Wang, Z
Hao, K
Hone, K
Wang, H
Keywords: Artificial immune system (AIS);Bidirectional optimization;Neural network (NN);Spinning process
Issue Date: 2014
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Citation: IEEE Transactions on Cybernetics, 44(2), 240 - 251, 2014
Abstract: A bidirectional optimizing approach for the melting spinning process based on an immune-enhanced neural network is proposed. The proposed bidirectional model can not only reveal the internal nonlinear relationship between the process configuration and the quality indices of the fibers as final product, but also provide a tool for engineers to develop new fiber products with expected quality specifications. A neural network is taken as the basis for the bidirectional model, and an immune component is introduced to enlarge the searching scope of the solution field so that the neural network has a larger possibility to find the appropriate and reasonable solution, and the error of prediction can therefore be eliminated. The proposed intelligent model can also help to determine what kind of process configuration should be made in order to produce satisfactory fiber products. To make the proposed model practical to the manufacturing, a software platform is developed. Simulation results show that the proposed model can eliminate the approximation error raised by the neural network-based optimizing model, which is due to the extension of focusing scope by the artificial immune mechanism. Meanwhile, the proposed model with the corresponding software can conduct optimization in two directions, namely, the process optimization and category development, and the corresponding results outperform those with an ordinary neural network-based intelligent model. It is also proved that the proposed model has the potential to act as a valuable tool from which the engineers and decision makers of the spinning process could benefit.
Description: This is the author's accepted manuscript (under the provisional title "Bi-directional optimization of the melting spinning process with an immune-enhanced neural network"). The final published article is available from the link below. Copyright 2014 @ IEEE.
URI: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6615923
http://bura.brunel.ac.uk/handle/2438/8485
DOI: http://dx.doi.org/10.1109/TSMCC.2013.2252896
ISSN: 2168-2267
Appears in Collections:Publications
Computer Science
Dept of Computer Science Research Papers

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