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Handan, China

Hebei University of Engineering is a provincial university based in Handan, Hebei province, China.It was established in 2003 from the amalgamation of individual colleges; Hebei Institute of Architectural Science and Technology, North China Institute of Water Conservancy and Hydro-electric Power, Handan Medicine College and Handan Agriculture College.In 2006, Ministry of Education of China authorized the university to changed its name to Hebei University of Engineering. The university now specializes in the fields of civil engineering, together with science disciplines, water power, agriculture and medicine. Wikipedia.


Wei J.,Hebei University of Engineering
Journal of Convergence Information Technology | Year: 2010

With respect to multiple attribute decision making problems with linguistic information of attribute values and weight values, a decision analysis is proposed. Then, a method based on the ET-WA operator for multiple attribute decision making is presented. In the approach, alternative appraisal values are calculated by the aggregation of 2-tuple linguistic information. Thus, the ranking of alternative or selection of the most desirable alternative(s) is obtained by the comparison of 2-tuple linguistic information. Finally, a numerical example with risk evaluation of high-technology is used to illustrate the applicability and effectiveness of the proposed method. Source


Hou J.,Hebei University of Engineering
Journal of Convergence Information Technology | Year: 2010

The aim of this paper is to investigate the multiple attribute decision making problems with intuitionistic fuzzy information, in which the information about attribute weights is incompletely known, and the attribute values take the form of intuitionistic fuzzy numbers. In order to get the weight vector of the attribute, we establish an optimization model based on the basic ideal of traditional grey relational analysis (GRA) method, by which the attribute weights can be determined. Then, based on the traditional GRA method, calculation steps for solving intuitionistic fuzzy multiple attribute decision-making problems with completely known weight information are given. The degree of grey relation between every alternative and positive ideal solution is calculated. Then, a relative relational degree is defined to determine the ranking order of all alternatives by calculating the degree of grey relation to both the positive-ideal solution (PIS). Finally, an illustrative example is given to verify the developed approach and to demonstrate its practicality and effectiveness. Source


Hou J.,Hebei University of Engineering
Journal of Convergence Information Technology | Year: 2010

With respect to multiple attribute decision making problem with triangular fuzzy linguistic information, in which the attribute weights and expert weights take the form of real numbers, and the preference values take the form of triangular fuzzy linguistic variables, a operator for aggregating triangular fuzzy linguistic variables, such as the fuzzy linguistic weighted harmonic mean (FLWHM) operator is introduced. Based on the FLWHM operators, a practical method is developed for group decision making with triangular fuzzy linguistic variables. Finally, an illustrative example about software selection is given to verify the developed approach. Source


Zhao W.,Hebei University of Engineering
Procedia Engineering | Year: 2011

To improve the adaptability and effect of image enhancement, this paper has proposed an image enhancement method based on Gravitational Search Algorithm (GSA), which is used for optimizing the parameters of the normalized incomplete Beta function using the characteristics of the original image, the acquired function is employed to enhance the degraded image. The simulation results show the method can effectively enhance the global contrast of the image and vision. So this method is practical in the field of gray level image adaptive enhancement. © 2011 Published by Elsevier Ltd. Source


Wei J.,Hebei University of Engineering
Journal of Convergence Information Technology | Year: 2010

The aim of this paper is to investigate the multiple attribute decision making problems with linguistic information, in which the information about attribute weights is incompletely known, and the attribute values take the form of linguistic variables. We develop a new method to solve linguistic MADM with incomplete weight. In order to get the weight vector of the attribute, we establish an optimization model based on the basic ideal of traditional TOPSIS, by which the attribute weights can be determined. Based on this model, we develop a TOPSIS method to rank alternatives and to select the most desirable one(s). Finally, an example is shown to highlight the procedure of the proposed algorithm at the end of this paper. Source

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