Zaozhuang, China

Zaozhuang University

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Zaozhuang, China
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Yang B.,Zaozhuang University
2017 7th International Workshop on Computer Science and Engineering, WCSE 2017 | Year: 2017

In this paper, an efficient identification method based on additive Legendre neural network (ALNN) model and hybrid evolutionary method is proposed to identify nonlineat systems. In order to improve efficiency of Legendre neural network (LNN), additive Legendre neural network is proposed. For finding the optimal structure and parameters of ALNN model, a new hybrid evolutionary method besed on binary particle swarm optimization (BPSO) algorithm and firefly algorithm is employed. Two nonlinear system identification experiments are used to test ALNN model. The results reveal that ALNN model performs better than LNN and other classic neural networks.


Yang B.,Zaozhuang University
IOP Conference Series: Materials Science and Engineering | Year: 2017

Accurate models play an important role in capturing the significant characteristics of the network traffic, analyzing the network dynamic, and improving the forecasting accuracy for system dynamics. In this study, complex-valued neural network (CVNN) model is proposed to further improve the accuracy of small-time scale network traffic forecasting. Artificial bee colony (ABC) algorithm is proposed to optimize the complex-valued and real-valued parameters of CVNN model. Small-scale traffic measurements data namely the TCP traffic data is used to test the performance of CVNN model. Experimental results reveal that CVNN model forecasts the small-time scale network traffic measurement data very accurately. © Published under licence by IOP Publishing Ltd.


Juan L.,Zaozhuang University
2017 3rd International Conference on Information Management, ICIM 2017 | Year: 2017

Zaozhuang city in Shandong province is changing from the mining city to the tourist city, the tourism industry is developing rapidly, but the tourism management is relatively backward. In order to provide technical support for Zaozhuang tourism management, according to the characteristics of tourism resources in Zaozhuang, the author designs and develops the tourism resources management system. Combined with Access database, using GIS technology, in VB development platform for system development, the system has the advantages of short development cycle, simple and quick. The system can provide detailed information query management services to meet the needs of managers. © 2017 IEEE.


Gou Y.,Zaozhuang University
AIP Conference Proceedings | Year: 2017

A new type of power plant. i.e, Electric Power Confined Piston Engine, is invented by combining the free piston engine and the crank connecting rod mechanism of the traditional internal combustion engine. Directly using the reciprocating movement of the piston, this new engine converts the heat energy produced by fuel to electrical energy and output it. The paper expounds the working mechanism of ECPE and establishes the kinematics and dynamics equations. Furthermore, by using the analytic method, the ECPE electromagnetic force is solved at load cases. Finally, in the simulation environment of MARLAB, the universal characteristic curve is obtained in the condition of rotational speed n between 1000 r/min and 2400 r/min, throttle opening α between 30% and 100%. © 2017 Author(s).


You Z.,Zaozhuang University
Chemical Engineering Transactions | Year: 2017

As a kind of detection technology based on optical characteristics, spectral detection technology overcomes the defects of traditional detection technology. The common spectrum detection techniques include hyperspectral imaging, Raman spectroscopy and infrared spectroscopy. As a new detection technology, the detection efficiency is high and the time is short. It is easy to realize automation and is suitable for on-line detection of mass production. In the process of yeast culture, the content of glycerol and methanol were monitored in real time. The results show that the application of infrared spectrum detection technology and ATR probe can realize off-line and on-line monitoring of glycerol and methanol. The correlation coefficients of infrared prediction model were 98.65% and 98.09%, respectively. The results showed that it costed 40 hours from the culture stage to the beginning of the addition of glycerol. The time required for methanol consumption was 6 hours. The experimental results proved the possibility of the application of infrared detection technology in the industrial on-line monitoring. Copyright © 2017, AIDIC Servizi S.r.l.


Wang X.,Zaozhuang University
Proceedings - 2012 5th International Conference on Intelligent Computation Technology and Automation, ICICTA 2012 | Year: 2012

Today the independent component analysis (ICA) has been widely used in the blind source separation (BSS) to separate independent components in a data set based on its statistical properties. However, when the dimension of the input data is too high, the performance of the ICA may be not satisfactory. To address this problem, the present paper has proposed the new integrated method for the independent component extraction. The supervised manifold learning was firstly adopted to reduce the dimension of the input data, and then the kernel ICA (KICA) was employed to extract useful independent components in an efficient manner. The application of the proposed method has been successfully applied to the face image recognition. The experimental analysis has showed satisfactory and effective face image identification performance. © 2012 IEEE.


In this paper, we present a descent decomposition method for solving variational inequalities in equilibrium modeling, which can be viewed as an extension of the decomposition method proposed by Gabay and Mercier [4,5] by performing an additional projection step at each iteration. An optimal step length is employed to reach substantial progress. Under certain conditions, the global convergence of the descent method is proved. Preliminary numerical experiments are included to illustrate the efficiency of the new method. © 2011.


Xiao R.,Zaozhuang University | Yang W.,Zaozhuang University
Renewable Energy | Year: 2013

Biomass pyrolysis experiments were performed in a tubular reactor at different temperatures, the effects of which on organic structure of semi-char and tar had been investigated. Fourier-transform infrared (FTIR) analysis was conducted by a Nicolet 6700 FTIR spectrometer. The tar components at different temperatures were analyzed by GC/MS. It was observed that pyrolysis of biomass mainly occurs in the temperature range of 300-600 °C. A high temperature favored the production of gases. The yield of semi-char and the contained organic functional groups(C. O, C. C, C-H, C-O and OH) decreases significantly with the increasing final temperature. The tar yield passes through a maximum at about 500 °C. The organic functional groups in tar were stable but the transmittance of these groups decreased with the increasing final temperature. © 2012 Elsevier Ltd.


Liu Z.,Zaozhuang University
Optics Communications | Year: 2012

An adaptive image interpolation approach is proposed in this paper. The proposed approach imposes a regularization on the reconstructed high-resolution image to suppress the noise and blurring incurred in the observed low-resolution image. Furthermore, the proposed regularization scheme is steered by the local gradient information of the image, which is evaluated using a probabilistic measure. Experiments are conducted to demonstrate the superior performance of the proposed approach. © 2011 Elsevier B.V. All rights reserved.


Wang Y.,Zaozhuang University
ICIME 2010 - 2010 2nd IEEE International Conference on Information Management and Engineering | Year: 2010

So far, feather and down category recognition is often done by man with a microscope, but this method has some disadvantages. So a feather and down category recognition system is proposed in the paper [1], and then feather and down category recognition can be done by computer automatically. After the image processing and segmentation using GA, the triangle node of two-value image of feather and down is to be recognized with SVM, then the triangle nodes which have been recognized will be matched and the distance between the matched triangle nodes is calculated, in the end, the feather and down category is recognized. After lots of experiments, it is found that the recognition rate is lower than artificial recognition. In order to improving recognition rate, RBF kernel SVM and MOAA SVM are introduced into the recognition system, and a revised feather and down recognition model is put forward. It is shown that it is efficient to feather and down recognition. © 2010 IEEE.

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