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Business Intelligence and Financial Engineering, 2009. BIFE '09. International Conference on

Date 24-26 July 2009

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Displaying Results 1 - 25 of 209
  • [Front cover]

    Publication Year: 2009, Page(s): C1
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  • [Title page i]

    Publication Year: 2009, Page(s): i
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  • [Title page iii]

    Publication Year: 2009, Page(s): iii
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  • [Copyright notice]

    Publication Year: 2009, Page(s): iv
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  • Table of contents

    Publication Year: 2009, Page(s):v - xviii
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  • Preface

    Publication Year: 2009, Page(s):xix - xx
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  • Organizing Committee

    Publication Year: 2009, Page(s): xxi
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  • Program Committee

    Publication Year: 2009, Page(s):xxii - xxiv
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  • Workshop Co-chairs

    Publication Year: 2009, Page(s): xxv
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  • list-reviewer

    Publication Year: 2009, Page(s):xxvi - xxvii
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  • An Algorithm for Determining Neural Network Architecture Using Differential Evolution

    Publication Year: 2009, Page(s):3 - 7
    Cited by:  Papers (6)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (287 KB) | HTML iconHTML

    Artificial neural networks (ANNs) have been applied to a variety of classification and learning tasks. The use of evolutionary algorithms (EA) as one of the fastest, robust and efficient global search techniques has allowed different properties of artificial neural networks to be evolved. This paper proposes the possibility of using differential evolution for determining an ANN architecture (DNNA)... View full abstract»

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  • Predicting China's Energy Consumption Using Artificial Neural Networks and Genetic Algorithms

    Publication Year: 2009, Page(s):8 - 11
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (288 KB) | HTML iconHTML

    In this work, artificial neural networks (ANN) based on genetic algorithm (GA) have been developed to predict energy consumption in China. The numbers of neurons in the hidden layer, the momentum rate and the learning rate are determined using the genetic algorithm. The inputs to the artificial neural networks model are four variables, namely, gross domestic product, industrial structure, total po... View full abstract»

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  • Stock Bubbles' Nature: A Cluster Analysis of Chinese Shanghai a Share Based on SOM Neural Network

    Publication Year: 2009, Page(s):12 - 16
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (291 KB) | HTML iconHTML

    The stock market bubbles present different properties in different economic environments and stages, and their impacts on the economic system are varied. In this paper, self organizing map (SOM) and principal component analysis (PCA) were employed to determine the property of the stock bubbles in Shanghai stock market from Jan-2000 to Apr-2008. The nature of the bubbles was interpreted by factor a... View full abstract»

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  • The Application of Artificial Neural Networks in Risk Assessment on High-Tech Project Investment

    Publication Year: 2009, Page(s):17 - 20
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (226 KB) | HTML iconHTML

    Investment risks assessment of high-tech projects is a more complex process, involving various factors and it is not entirely the linear relationship between influencing factors and measurement results. Artificial neural network (ANN) has a strong nonlinear mapping ability, with strong learning ability and high classification and prediction accuracy. The paper applied ANN to establish a new risk a... View full abstract»

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  • IPO Pricing of SME Based on Artificial Neural Network

    Publication Year: 2009, Page(s):21 - 24
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (235 KB) | HTML iconHTML

    The pricing method of new shares issuing based on artificial neural network is studied in this paper. A three-layer neural network model is established and simulation tests are carried out. It shows that the BP network model established fits well with the real first day's closing price of stock and greatly improves the IPO pricing. It provides a new way to investors for forecasting IPO price of sm... View full abstract»

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  • Appraisal of High-Tech Zone Technology Innovation Ability Based on BP Neural Network

    Publication Year: 2009, Page(s):25 - 28
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (235 KB) | HTML iconHTML

    High-tech industry zone play a important role in the global economic system with the continuously new knowledge innovation, itpsilas becoming the main motion of regional economic structure optimization and competition. The technology ability and diffuse effect of High-tech zone influence itself and regional economic development greatly. This paper design High-tech zone technology innovation abilit... View full abstract»

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  • The Finger Movement Identification Based on Fuzzy Clustering and BP Neural Network

    Publication Year: 2009, Page(s):29 - 33
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (252 KB) | HTML iconHTML

    The classification and identification technology plays an important role in the research of brain-computer interface (BCI) systems. In this paper, we do fuzzy clustering disposal for the multi-channel electroencephalogram (EEG) during finger movement at first according to event-related desynchronization phenomena (ERD) in the event-related EEG. Then we classify signal-trial EEG with the feature ex... View full abstract»

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  • An Application of Hopfield Neural Network in Target Selection of Mergers and Acquisitions

    Publication Year: 2009, Page(s):34 - 37
    Cited by:  Papers (3)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (263 KB) | HTML iconHTML

    Target selection is one of the most important steps of during the process of mergers and acquisitions. Hopfield neural network is very strong in pattern recognition which can simulate the criteria of acquirer and remind it. The network model overcomes the shortcomings of classic statistic and fuzzy models and embodies the requirements of acquirer. Demonstration shows that Hopfield network is an ef... View full abstract»

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  • Modelling and Prediction of the CNY Exchange Rate Using RBF Neural Network

    Publication Year: 2009, Page(s):38 - 41
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (326 KB) | HTML iconHTML

    The CNY exchange rates can be viewed as financial time series which are charactered by high uncertainty, nonlinearity and time-varying behavior. Predictions for exchange rates of GBP-CNY and USD-CNY were carried respectively by means of RBF neural network forecasters. The detailed designs for architectures of RBF neural network models, transfer functions of the hidden layer nodes, input vectors an... View full abstract»

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  • A Method of Gear Fault Diagnosis Based on CWT and ANN

    Publication Year: 2009, Page(s):42 - 45
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (249 KB) | HTML iconHTML

    Aimed at the engine rotor fault, a new diagnosis method based on Wavelet Transform and artificial neural network (ANN) is proposed. Firstly, according to the wavelet transform theories, the original signals are sampling repeatedly, and the continuous wavelet transform (CWT) is used for the signals sampled. Afterward, the obtained signals are decomposed to fixed layer so as to obtain the frequency ... View full abstract»

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  • Research of Dispatching Method in Elevator Group Control System Based on Traffic Mode Identify

    Publication Year: 2009, Page(s):46 - 49
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (259 KB) | HTML iconHTML

    Elevator group control system (EGCS) with multi-objective, stochastic and nonlinear characteristics is a complex optimization system. After analyzing characteristic of typical traffic mode of elevator. This paper proposed a new simulation platform of an elevator group control system implemented in C# using the fuzzy-neural network technology. The result of simulation shows that this method realize... View full abstract»

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  • Power Futures Price Forecasting Based on RBF Neural Network

    Publication Year: 2009, Page(s):50 - 52
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (211 KB) | HTML iconHTML

    In order to forecast power futures price exactly, a radial basis function neural network (RBF NN) method is used in this paper. The RBF NN method has the advantages of rapid training, generality and simplicity over feed-forward neural network. The data of Nordic electricity market is adopted for case analysis. Empirical results reveal that the RBF NN method has a more accurate result than back-pro... View full abstract»

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  • Personal Credit Rating Assessment for the National Student Loans Based on Artificial Neural Network

    Publication Year: 2009, Page(s):53 - 56
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (244 KB) | HTML iconHTML

    National student Loans are the use of the financial means to improve the college subsidy policy. State Student Loan is a personal credit loan, but the personal credit assessment system of commercial banks could not make a correct assessment for a college Studentpsilas credit rating because the students have no records about their credit. To avoid the credit risk, it must to establish a rational cr... View full abstract»

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  • Integration of Unascertained Method and Neural Networks in Financial Early Warning

    Publication Year: 2009, Page(s):57 - 60
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (254 KB) | HTML iconHTML

    Unascertained system that imitates the human brain's thinking logical is a kind of mathematical tools used to deal with imprecise and uncertain knowledge. Artificial neural network that imitates the function of human neurons may function as a general estimator, mapping the relationship between input and output. Combination of these two methods were made attemption in financial early warning in thi... View full abstract»

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  • Anti-dumping Early-Warning Model Based on Entropy Weight and SOM

    Publication Year: 2009, Page(s):61 - 64
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (243 KB) | HTML iconHTML

    A new anti-dumping early-warning system for the export of China's products is presented, which is based on entropy weight method and SOM neutral network. It is different from traditional modeling methods. We can acquire the indexpsila weight by entropy method, and then, the indexes in which the weight are decided are used to develop classification rules and train SOM nerve network. The result of t... View full abstract»

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