The Evaluation of Fabric Prickle Based on BP Neural Network
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A three-layer BP neural network model was established by relating subjective evaluation of fabric prickle level and 16 objective parameters from KES-FB system. The elastic gradient decrease method was adopted for network training to achieve the preset precision of the model which was later applied to fabric prickle level evaluation. Results from this method gave a considerably accuracy compared with actual subjective results which implied a compatibility between BP neural network and traditional subjective evaluation.
2013 ◽
Vol 415
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pp. 569-573
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2021 ◽
Vol 1744
(4)
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pp. 042232
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2010 ◽
Vol 34-35
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pp. 301-305
2017 ◽
Vol 19
(2)
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pp. 878-893
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