Next Article in Journal
Accurate Measurement of Magnetic Resonance Imaging Gradient Characteristics
Previous Article in Journal
Implications of Surface and Bulk Properties of Abutment Implants and Their Degradation in the Health of Periodontal Tissue
Materials 2013, 6(12), 5967-5985; doi:10.3390/ma6125967
Article

Performance Prediction of Differential Fibers with a Bi-Directional Optimization Approach

1
,
1,2,* , 1,2
,
1
 and
1
1 College of Information Sciences and Technology, Donghua University, Shanghai 201620, China 2 Engineering Research Center of Digitized Textile & Fashion Technology, Ministry of Education, Donghua University, Shanghai 201620, China
* Author to whom correspondence should be addressed.
Received: 6 November 2013 / Revised: 2 December 2013 / Accepted: 11 December 2013 / Published: 18 December 2013
Download PDF [632 KB, uploaded 18 December 2013]

Abstract

This paper develops a bi-directional prediction approach to predict the production parameters and performance of differential fibers based on neural networks and a multi-objective evolutionary algorithm. The proposed method does not require accurate description and calculation for the multiple processes, different modes and complex conditions of fiber production. The bi-directional prediction approach includes the forward prediction and backward reasoning. Particle swam optimization algorithms with K-means algorithm are used to minimize the prediction error of the forward prediction results. Based on the forward prediction, backward reasoning uses the multi-objective evolutionary algorithm to find the reasoning results. Experiments with polyester filament parameters of differential production conditions indicate that the proposed approach obtains good prediction results. The results can be used to optimize fiber production and to design differential fibers. This study also has important value and widespread application prospects regarding the spinning of differential fiber optimization.
Keywords: bi-directional prediction; neural networks; multi-objective evolutionary algorithm; performance prediction; differential fibers bi-directional prediction; neural networks; multi-objective evolutionary algorithm; performance prediction; differential fibers
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Share & Cite This Article

Further Mendeley | CiteULike
Export to BibTeX |
EndNote
MDPI and ACS Style

Wang, Y.; Ding, Y.; Hao, K.; Wang, T.; Liu, X. Performance Prediction of Differential Fibers with a Bi-Directional Optimization Approach. Materials 2013, 6, 5967-5985.

View more citation formats

Related Articles

Article Metrics

For more information on the journal, click here

Comments

Cited By

[Return to top]
Materials EISSN 1996-1944 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert