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Computational Sciences and Optimization, 2009. CSO 2009. International Joint Conference on

Date 24-26 April 2009

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  • [Front cover - Vol 2]

    Publication Year: 2009, Page(s): C1
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  • [Title page i - Volume 2]

    Publication Year: 2009, Page(s): i
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  • [Title page iii - Volume 2]

    Publication Year: 2009, Page(s): iii
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  • [Copyright notice - Volume 2]

    Publication Year: 2009, Page(s): iv
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  • Table of contents - Volume 2

    Publication Year: 2009, Page(s):v - xxi
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  • Preface - Volume 2

    Publication Year: 2009, Page(s):xxii - xxiii
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  • Organizing Committee - Volume 2

    Publication Year: 2009, Page(s): xxiv
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  • Program Committee - Volume 2

    Publication Year: 2009, Page(s):xxv - xxviii
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  • Workshop Co-chairs - Volume 2

    Publication Year: 2009, Page(s): xxix
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  • Co-sponsors - Volume 2

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

    Publication Year: 2009, Page(s): xxxi
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  • Recognition of a Sucker Rod's Defect with ANN and SVM

    Publication Year: 2009, Page(s):3 - 6
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (540 KB) | HTML iconHTML

    In order to improve the recognition rate of a sucker rod's defect and reduce the rapture possibility of the rod, the mixed characters include of wavelet packet energy character and the peak value in the time-domain were used as the input of a recognition network, and artificial neural networks (ANN) and support vector machines (SVM) were used and compared as the recognition network to get the best... View full abstract»

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  • Weighted LS-SVM Credit Scoring Models with AUC Maximization by Direct Search

    Publication Year: 2009, Page(s):7 - 11
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (489 KB) | HTML iconHTML

    Credit scoring models are very important tools for credit granting institutions to assess the credit risk of their customers. Most previous researches focus on improving predictive accuracy of models. In this research, a weighted LS-SVM credit scoring model with Area under ROC curve maximization is proposed and optimized by direct search. The tests on two real-world datasets show that it is effect... View full abstract»

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  • Crude Oil Price Prediction Using Slantlet Denoising Based Hybrid Models

    Publication Year: 2009, Page(s):12 - 16
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (356 KB) | HTML iconHTML

    The accurate prediction of crude oil price movement has always been the central issue with profound implications across different levels of the economy. This study conducts empirical investigations into the characteristics of crude oil market and proposes a novel Slantlet denoising based hybrid methodology for the prediction of its movement. The proposed algorithm models the underlying data charac... View full abstract»

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  • A Statistical Neural Network Approach for Value-at-Risk Analysis

    Publication Year: 2009, Page(s):17 - 21
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (353 KB) | HTML iconHTML

    This study develops a new methodology based on ANN for Value-at-Risk (VaR) modeling. Specifically, we propose a statistical procedure for ANN model selection. The statistical ANN deals with each layer individually and estimates the weights of subsequent layer with those of preceding layers fixed. This allows the derivation of statistical theory for model selection, which reduces the need to fit a ... View full abstract»

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  • Simulated Annealing Based Rule Extraction Algorithm for Credit Scoring Problem

    Publication Year: 2009, Page(s):22 - 26
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (409 KB) | HTML iconHTML

    This paper presents a simulated annealing based rule extraction algorithm (SAREA) for credit scoring problems. In previous studies, several classification algorithms like statistical models, mathematical programming, and artificial intelligence techniques have been used. This paper aims to illustrate the ability of SA to develop accurate classifiers for credit scoring problems. The use of SA is a ... View full abstract»

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  • A Neural Network Ensemble Prediction Model Based on MGF and PLS for Drought and Waterlogging Disasters in Short-Range Climate

    Publication Year: 2009, Page(s):29 - 33
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (338 KB) | HTML iconHTML

    Taking the mean precipitation from 16 stations spread around the south China during the pre-flood season as the prediction object treated by Empirical Orthogonal Function (EOF) method, previous physical predictors and factors that reflected the significant period of predictands by means of the Mean Generating Functions (MGF) technique, were extracted useful information for prediction by using Part... View full abstract»

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  • A Summer Precipitation FNN Multi-step Prediction Model Based on SSA-MGF

    Publication Year: 2009, Page(s):34 - 38
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (360 KB) | HTML iconHTML

    A fuzzy neural network (FNN) multi-step prediction model based on singular spectrum analysis (SSA) and mean generating function (MGF) for summer precipitation has been developed in this paper. In the modeling process, the original standardized sample series of summer precipitation was denoised and reconstructed with SSA, the extended matrix of MGF of the reconstructed precipitation series (as the ... View full abstract»

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  • Application of Fuzzy Neural Network to the Flood Season Precipitation Forecast

    Publication Year: 2009, Page(s):39 - 43
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (369 KB) | HTML iconHTML

    Taking the flood season (from May to October) precipitation in Hainan province as the forecast object, the application of fuzzy neural networks forecasting method with different forecast factors is studied. The results show that the new model based on principal component analysis is significantly superior to the traditional stepwise regression model and other fuzzy neural networks models which sel... View full abstract»

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  • A Novel Artificial Neural Network Ensemble Model Based on K--Nearest Neighbor Nonparametric Estimation of Regression Function and Its Application for Rainfall Forecasting

    Publication Year: 2009, Page(s):44 - 48
    Cited by:  Papers (6)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (402 KB) | HTML iconHTML

    In this paper, a novel artificial neural network ensemble rainfall forecasting model is proposed for rainfall forecasting based on K-nearest neighbor nonparametric estimation of regression. In this model, original data set are partitioned into some different training subsets via Bagging technology. Then different ANN algorithms and different network architecture generate diverse individual neural ... View full abstract»

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  • Bayesian Neural Network Ensemble Model Based on Partial Least Squares Regression and Its Application in Rainfall Forecasting

    Publication Year: 2009, Page(s):49 - 52
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (379 KB) | HTML iconHTML

    Rainfall forecasting is an essential tool in order to reduce the risk to life and alleviate economic losses. In this paper, using Bayesian techniques design a neural network ensemble model for rainfall forecasting. Firstly, using Bagging techniques and the different neural network algorithm are applied so as to generate an ensemble individual. and then the Partial Least Square regression technique... View full abstract»

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  • Decision Making Meteorological Services System Based on Geographic Information System

    Publication Year: 2009, Page(s):53 - 55
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (377 KB) | HTML iconHTML

    The framework and the main features of the decision-making meteorological services system (DMMS), based on component GIS technology, are first introduced. Then some key issues of GIS application to system are discussed. At last, we draw some conclusions and make sure that this system can also bring a good construction idea of the decision-making meteorological services system all over the China. View full abstract»

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  • Application of Nonparametric Methods in Short-Range Precipitation Forecasting

    Publication Year: 2009, Page(s):56 - 58
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (327 KB) | HTML iconHTML

    Short-range precipitation forecasting plays a key role in developing public affairs. Seasonal autoregressive integrated moving average (ARIMA), a classic parametric modeling approach to time series, and nonparametric regression models have been proposed as well suited for application to short-range precipitation forecasting. In this paper, the method of the k-nearest neighbor estimation in the non... View full abstract»

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  • The Distribution Characteristic of Travel Time Reliability in Beijing Road Network

    Publication Year: 2009, Page(s):61 - 63
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (363 KB) | HTML iconHTML

    To evaluate the reliability of the road network, the paper designed a mathematic model of travel time reliability index. Using the travel time reliability index, the paper analyzed the temporal and spatial distribution characteristics of Beijing road network reliability based on the floating car data. The results show that the travel time reliability is the lowest at the afternoon peak hour and th... View full abstract»

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  • Synchronized Traffic Flow and Metastable States from the Perspective of Constant Time Headway

    Publication Year: 2009, Page(s):64 - 68
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1790 KB) | HTML iconHTML

    In the past decade, perhaps one of the most important findings in traffic flow field is the "synchronized flow''. In previous literature, various mechanisms have been presented to explain synchronized flow. This paper proposes that trying to keep a constant time headway might be another possible origin of synchronized flow. The simulation of this effect is performed based on a cellular automaton m... View full abstract»

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