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DC Field | Value | Language |
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dc.contributor.author | Liang, X | - |
dc.contributor.author | Ding, Y | - |
dc.contributor.author | Wang, Z | - |
dc.contributor.author | Hao, K | - |
dc.contributor.author | Hone, K | - |
dc.contributor.author | Wang, H | - |
dc.date.accessioned | 2014-05-20T14:12:45Z | - |
dc.date.available | 2014-05-20T14:12:45Z | - |
dc.date.issued | 2014 | - |
dc.identifier.citation | IEEE Transactions on Cybernetics, 44(2), 240 - 251, 2014 | en_US |
dc.identifier.issn | 2168-2267 | - |
dc.identifier.uri | http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6615923 | en |
dc.identifier.uri | http://bura.brunel.ac.uk/handle/2438/8485 | - |
dc.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. | en_US |
dc.description.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. | en_US |
dc.description.sponsorship | National Nature Science Foundation of China, Ministry of Education of China, the Shanghai Committee of Science and Technology), and the Fundamental Research Funds for the Central Universities. | en_US |
dc.language | English | - |
dc.language.iso | en | en_US |
dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) | en_US |
dc.subject | Artificial immune system (AIS) | en_US |
dc.subject | Bidirectional optimization | en_US |
dc.subject | Neural network (NN) | en_US |
dc.subject | Spinning process | en_US |
dc.title | Bidirectional optimization of the melting spinning process | en_US |
dc.type | Article | en_US |
dc.identifier.doi | http://dx.doi.org/10.1109/TSMCC.2013.2252896 | - |
pubs.organisational-data | /Brunel | - |
pubs.organisational-data | /Brunel/Administration and Support Staff | - |
pubs.organisational-data | /Brunel/Administration and Support Staff/Administration and Support Staff | - |
pubs.organisational-data | /Brunel/Brunel Active Staff | - |
pubs.organisational-data | /Brunel/Brunel Active Staff/School of Info. Systems, Comp & Maths | - |
pubs.organisational-data | /Brunel/Brunel Active Staff/School of Info. Systems, Comp & Maths/Computer Science | - |
pubs.organisational-data | /Brunel/University Research Centres and Groups | - |
pubs.organisational-data | /Brunel/University Research Centres and Groups/Brunel Business School - URCs and Groups | - |
pubs.organisational-data | /Brunel/University Research Centres and Groups/Brunel Business School - URCs and Groups/Centre for Research into Entrepreneurship, International Business and Innovation in Emerging Markets | - |
pubs.organisational-data | /Brunel/University Research Centres and Groups/School of Arts - URCs and Groups | - |
pubs.organisational-data | /Brunel/University Research Centres and Groups/School of Arts - URCs and Groups/Brunel Centre for Contemporary Writing | - |
pubs.organisational-data | /Brunel/University Research Centres and Groups/School of Health Sciences and Social Care - URCs and Groups | - |
pubs.organisational-data | /Brunel/University Research Centres and Groups/School of Health Sciences and Social Care - URCs and Groups/Brunel Institute for Ageing Studies | - |
pubs.organisational-data | /Brunel/University Research Centres and Groups/School of Health Sciences and Social Care - URCs and Groups/Brunel Institute of Cancer Genetics and Pharmacogenomics | - |
pubs.organisational-data | /Brunel/University Research Centres and Groups/School of Health Sciences and Social Care - URCs and Groups/Centre for Systems and Synthetic Biology | - |
pubs.organisational-data | /Brunel/University Research Centres and Groups/School of Information Systems, Computing and Mathematics - URCs and Groups | - |
pubs.organisational-data | /Brunel/University Research Centres and Groups/School of Information Systems, Computing and Mathematics - URCs and Groups/Centre for Information and Knowledge Management | - |
pubs.organisational-data | /Brunel/University Research Centres and Groups/School of Information Systems, Computing and Mathematics - URCs and Groups/Multidisclipary Assessment of Technology Centre for Healthcare (MATCH) | - |
pubs.organisational-data | /Brunel/University Research Centres and Groups/School of Information Systems, Computing and Mathematics - URCs and Groups/People and Interactivity Research Centre | - |
Appears in Collections: | Publications Computer Science Dept of Computer Science Research Papers |
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