Hunan University of Finance and Economics

Changsha, China

Hunan University of Finance and Economics

Changsha, China

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Xiao Y.H.,Hunan University of Finance and Economics
Applied Mechanics and Materials | Year: 2014

Our country has many serious problems such as fake-licensed vehicle, stolen vehicle, overloaded vehicle, over speed vehicle and so on at present. This paper designs and realizes a kind of intelligent vehicle inspection system based on RFID technology in order to solve these problems. This system obtain the all kinds of vehicle information by recognizing electronic label card and deal with all kinds of information in the background in order to manage vehicle. The system has changed the traditional manual vehicle management mode and realized automated inspection without parking. It can reduce the work intensity of law-enforcement personal and take the initiative to call the police when meet all kinds of illegal vehicle, stolen vehicle etc. It can eliminate the crime motive and behavior. It provides the great help for social and economic development. © (2014) Trans Tech Publications, Switzerland.

Fu S.,Hunan University of Finance and Economics
Journal of Software Engineering | Year: 2016

For grey stochastic multi-criteria decision-making problem with criterion value as extended grey number, the study proposes grey stochastic multi-criteria decision-making approach based on Hausdorff distance. First, it provides definition and operation ruleof extended grey number stochastic variable and expectation, then obtains expectation decision matrix about grey number based on grey decision matrix and natural state probability. Second, the study calculates distance between the various solutions and positive and negative ideal solutions, respectively by combining weight vector of various criteria and ultimately determines the relative closeness degree and sorts the solution based on the value. Finally, through information system evaluation, the study results verify feasibility and effectiveness of the proposed method. © 2016 Sha Fu.

Zhu S.P.,Hunan University of Finance and Economics
Applied Mechanics and Materials | Year: 2014

In this paper, we propose an effective approach for detecting moving vehicles in nighttime traffic scenes. We use Multiple Instance Learning method to automatically detect vehicle from video sequences by constructing the Multiple Instance Learning model at nighttime. At first, we extract SIFT feature using SIFT feature extraction algorithm, which is used to characterize moving vehicles at nighttime. Then Multiple Instance Learning model is used for the on-road detection of vehicles at nighttime, in order to improve the detection accuracy, the class label information was used for the learning of the Multiple Instance Learning model. Final experiments were performed and evaluate the proposed method at nighttime under urban traffic condition, the experiment results show that the average detection accuracy is over 96. 2%, which validates that the proposed vehicle detection approach is feasible and effective for the on-road detection of vehicles at nighttime and identification in various nighttime environments. © (2014) Trans Tech Publications, Switzerland.

Yan H.-Y.,Hunan University of Finance and Economics
Procedia Engineering | Year: 2011

The construction project bid evaluation is a typical multi-objective decision-making problem. Considering the content of the construction project bid evaluation, an appraisal index system of the construction project bid evaluation was established; The reasonable range of index values which can reflect the tenderer preference was utilized to perform standardization of evaluation indicators; The optimal grey relational grades for bidder were determined by gray relational model, and the optimal decision-making conclusion for bid evaluation was made after comparison of the optimal grey relational grades. The model had the advantages of complementary of theory and experience, strong operability and scientific quantify, therefore popularized the grey correlation model application in construction project. © 2011 Published by Elsevier Ltd.

Xiang H.,Hunan University of Finance and Economics
Industrial, Mechanical and Manufacturing Science - Proceedings of the 2014 International Conference on Industrial, Mechanical and Manufacturing Science, ICIMMS 2014 | Year: 2015

Nowadays, CPA firms’ accounting and audit quality are challenged by greater diversity and uncertainty in financial contents of enterprises and institutions, aswell as anthropogenic negative energy existing in actual practices. In order to confront this challenge, a CPA firm should make adjustments in 3 aspects, i.e., inherent internal control, internal and external related accounting lawand regulation, and integrated management model. Thiswork discussed CAP firms’quality control model in the current situation to improve their accounting and audit quality. © 2015 Taylor & Francis Group, London.

Huiqun H.,Hunan University of Finance and Economics | Guang S.,Hunan University of Finance and Economics
Advances in Information Sciences and Service Sciences | Year: 2012

Improperly selected ERP software may have an impact on the time required, and the costs and market share of a company, selecting the best desirable ERP software has been the most critical problem for a long time. On the other hand, selecting ERP software is a multiple-criteria decision-making (MCDM) problem, and in the literature, many methods have been introduced to evaluate this kind of problem, which has been widely used in MCDM selection problems. In this paper, an integrated approach of ERP software selection analytic hierarchy process improved by rough sets theory (Rough-AHP) and fuzzy TOPSIS method is proposed to obtain final ranking.

Fu S.,Hunan University of Finance and Economics
Mathematical and Computational Applications | Year: 2015

Aiming at complexity and uncertainty of actual decision-making environment, thisstudyproposes a multipleattribute decision-making model of grey target basedon positive and negative bull's-eye. Firstly, itdefines thatthe optimal effect vectorand the worst effect vector ofgrey target decision are respectively positive, negative bull's-eye of the grey target; secondly, comprehensively considering the space projection distance between various schemes and the positive and negative bull's-eye, it takesbull's-eye distance as the basis for space analysisand obtains a new integrated bull's-eye distance; then, in accordance with the comprehensive guidelines to minimize the bull's-eye distance, itconstructs goalprogrammingmodel forgoalfunction, and thus solvesthe index weight. Finally, through case studies of selective purchase ofinformation system, it verifies feasibility and effectiveness of the proposed grey target decision-making model.

Zhu S.,Hunan University of Finance and Economics
International Journal on Smart Sensing and Intelligent Systems | Year: 2015

Automatic facial expression recognition from video sequence is an essential research area in the field of computer vision. In this paper, a novel method for recognition facial expressions is proposed, which includes two stages of facial expression feature extraction and facial expression recognition. Firstly, in order to exact robust facial expression features, we use Active Appearance Model (AAM) to extract the global texture feature and optical flow technique to characterize facial expression which is determined facial velocity information. Then, these two features are integrated and converted to visual words using "bag-of-words" models, and facial expression is represented by a number of visual words. Secondly, the Latent Dirichlet Allocation (LDA) model are utilized to classify different facial expressions such as "anger", "disgust", "fear", "happiness", "neutral", "sadness", and "surprise". The experimental results show that our proposed method not only performs stably and robustly and improves the recognition rate efficiently, but also needs the least dimension when achieves the highest recognition rate , which demonstrates that our proposed method is superior to others.

Li L.,Hunan University of Finance and Economics
Research Journal of Applied Sciences, Engineering and Technology | Year: 2014

The aim of this study is to propose a new target recognition method for the multi-sensor with multiple characteristics indexes. Coefficient of variation is used to determine the weights of characteristic indexes. The conceptions of ideal optimal and negative ideal vectors are given first and then normalized relative ratio is used to comprehensive evaluation value. Hence the rule of target recognition is given. The method can avoid the subjectivity of the weight of characteristic indexes and improve the objectivity and accuracy of target recognition. Finally, numerical simulation illustrates the effectiveness and feasibility of the proposed method. © Maxwell Scientific Organization, 2014.

Xiao R.,Hunan University of Finance and Economics
Communications in Computer and Information Science | Year: 2010

Web service composition is a promising solution for building distributed applications on the e-business processes. It has been recognized as a flexible way for resource sharing and application integration. As the number of functional similar Web services increases, how to select Web services that can best meet the requirements of the consumers becomes an ongoing research direction in Web service community. Quality of Service (QoS) is the main factor to differentiate them. It is imperative to provide service consumers with facilities for selecting the only web services for their requirement according to their non-functional characteristics or QoS. However, the selection process is too greatly complicated to meet the requirement of business process. All required component services need to be constructed into an optimizing solution to the business processes. In this paper, the key business process performance model (KBPP) is proposed, which describe the key performance of business with specific features, a new approach to optimize the service selecting based on KBPP is presented, and dynamic decision of key business process performances. This novel optimizing model and Simulative experiments are conducted to show the validity and efficiency of the service selection process in a dynamic and uncertain environment of web services. © 2010 Springer-Verlag.

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