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
Open AccessArticle

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

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.
Materials 2013, 6(12), 5967-5985; https://doi.org/10.3390/ma6125967
Received: 6 November 2013 / Revised: 2 December 2013 / Accepted: 11 December 2013 / Published: 18 December 2013
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. View Full-Text
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
Show Figures

Figure 1

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.

Show more citation formats Show less citations formats

Article Access Map by Country/Region

1
Only visits after 24 November 2015 are recorded.
Back to TopTop