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Wenkai Xu,Peng Zhao,Liqiao Ning 대한토목학회 2018 KSCE JOURNAL OF CIVIL ENGINEERING Vol.22 No.4
Train delay is an inevitable phenomenon in urban rail transit system, but it usually has ripple effects by propagating to other trainsand lines. In particular, last train delay has serious effect on transfer passengers’ regular trips. Transfer passengers from last trainsconcretely fall into two types in this paper: passengers transferring from the last train of feeder line to the last train of connecting line(LtoL) or from the last train of feeder line to un-last train of connecting line (LtoU). Then the last train network delay managementmodel is presented with two objectives: maximizing connecting passengers and minimizing Average Transfer Waiting Time (ATWT)of LtoL transfer passengers. To solve large-scale practical problems rapidly, an efficient genetic algorithm is designed based on thismodel. Finally, the Beijing subway network is taken as a case study to verify the effectiveness of this model. Under various last traindelay scenarios, the results show that the bi-objective model can increase the number of connections between last trains andconnecting passengers, meanwhile, there is a big decline in the ATWT of LtoL transfer passengers.
A Hybrid Method based on Dynamic Compensatory Fuzzy Neural Network Algorithm for Face Recognition
Wenkai Xu,이응주 제어·로봇·시스템학회 2014 International Journal of Control, Automation, and Vol.12 No.3
Human face recognition skills can make simultaneous use of a variety of information from the face, including information about the age, sex, race, identity, and even current mood of the person. In this paper, a hybrid method combined Eigenface-LDA with Dynamic Compensatory Fuzzy Neural Network (DCFNN) is proposed for face recognition. Eigenfaces-LDA algorithm is used for face image of dimensionality reduction and finding a best subspace for classification, the extracted feature will be considered as the input of DCFNN. An improved Dynamic Fuzzy Neural Network is proposed by combing Dynamic Fuzzy Neural Network and Compensatory Fuzzy Neural Network to solve the prob-lem of feature classification. The proposed method has been tested on ORL and Yale face database; the experimental results show that our method can reduce the dimension of facial features well and recognize faces that under different illumination, pose and expression accurately.
Wenkai Zhang,Yanshan Zhan,Xiuxiu Gao,Runming Li,Weiwei Zhu,Hao Xu,Baoying Liu,Xiaomin Fang,Yuanqing Xu,Tao Ding 한국고분자학회 2018 Macromolecular Research Vol.26 No.1
Herein, we report the effect of oxygen functionalities of graphene oxide on thermal activated polymerization and thermal properties of reactive benzoxazine nanocomposites. The numbers of oxygen moieties of graphene oxide (GO) are controlled by hydrothermal reduction. The polymerization behavior of benzoxazine monomer (BA-a) is studied by Fourier transform infrared spectroscopy, differential scanning calorimetry and rheological analysis. It is hypothesized that the GO not only exhibits accelerated effect on the polymerization of the BA-a, but also the oxygen moieties such as carboxyl groups of GO interact with the benzoxazine polymers, leading to several orders of magnitude increase in the chemoviscosity and modulus of composite system. Thermal conductivity of poly(BA-a)/GO composite increases from an initial value of ∼0.27 W/mK to 0.47 W/mK as the loading increases from 1 wt% to 6 wt% (enhancement factor up to 176%). Moreover, the nanocomposites display enhanced initial decomposition temperature and char yields as the degree of GO reduction increases.