{"title":"Applications of (G'/G)-expansion to Traveling Wave Solutions for Variant Boussinesq Equations","authors":"Wei Li, Chunlei Ruan","doi":"10.1109/CSO.2012.85","DOIUrl":"https://doi.org/10.1109/CSO.2012.85","url":null,"abstract":"The (G'/G)-expansion method can be used for constructing exact traveling wave solutions of nonlinear evolution equations, where G=G(ξ) satisfies a second order linear ordinary differential equation (LODE for short), by which the traveling wave solutions involving parameters for the variant Boussinesq equations are obtained. The traveling wave solutions are expressed by the hyperbolic functions, the trigonometric functions and the rational functions.","PeriodicalId":170543,"journal":{"name":"2012 Fifth International Joint Conference on Computational Sciences and Optimization","volume":"124 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116647491","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"On a Computational Method for Impact of Compressible Fluid","authors":"Shili Sun, Shiyan Sun, Jian Hu","doi":"10.1109/CSO.2012.13","DOIUrl":"https://doi.org/10.1109/CSO.2012.13","url":null,"abstract":"The initial stage of a compressible liquid jet impact onto an elastic plate is considered in the paper. A numerical model is built and the wave governing equation is approximated by a doubly asymptotic method. Theoretical solution at the impact instant is deduced through considering compressibility or not. Doubly approximation method is compared with the analytic solution by Korobkin and theoretical solution respectively, showing that this approximation method is efficient and accurate.","PeriodicalId":170543,"journal":{"name":"2012 Fifth International Joint Conference on Computational Sciences and Optimization","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123769977","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Design of the Variable Business Process Model Based on Message Computing","authors":"Qing Yao, Yuqing Sun","doi":"10.1109/CSO.2012.43","DOIUrl":"https://doi.org/10.1109/CSO.2012.43","url":null,"abstract":"In order to address the agile adjustment in functional activities in business process reengineering, a variable business process model is proposed to achieve a flexible and variable business process mode. Against the variability characteristics of the business process, variability modeling method is applied to messages which transfer between the functional activities. The logical calculation in messages is used to control flow structure by defining different message format and structure. The replacement relationships along with constraint relationships between activities and flow structures are defined to achieve the unity of process variability and stability. Process variability is achieved based on the different types of message content, with business process logic and implementation logic separated. A case applied to tourism services serves as a good practice example of the convenient support for business process adjustment of this model.","PeriodicalId":170543,"journal":{"name":"2012 Fifth International Joint Conference on Computational Sciences and Optimization","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122198876","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Prediction Model Base on Evolving Neural Network Using Genetic Algorithm Coupled with Simulated Annealing for Water-level","authors":"Hong Ding, Xianghui Li, Wen-fang Liao","doi":"10.1109/CSO.2012.203","DOIUrl":"https://doi.org/10.1109/CSO.2012.203","url":null,"abstract":"In this study, a nonlinear forecasting model is proposed in order to obtain accurate prediction results and ameliorate forecasting performances. In the model, the genetic algorithm (GA) is coupled with simulated annealing (SA) algorithms to evolve a back-propagation neural network (BPNN) algorithm, called GASANN. The new model's performance is compared with three individual forecasting models, namely weighting moving average (WMA), stepwise regression (SR) and autoregressive integrated moving average (ARIMA) models by forecasting yearly water level of Liujiang River, which is a watershed from Guangxi of China. The results show that the new model outperforms than the other models presented in this study in terms of the same evaluation measurements. Therefore the nonlinear model proposed here can be used as an alternative forecasting tool for water level to achieve greater forecasting accuracy and improve prediction quality further.","PeriodicalId":170543,"journal":{"name":"2012 Fifth International Joint Conference on Computational Sciences and Optimization","volume":"97 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130420195","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Application of Hybrid RBF Neural Network Ensemble Model Based on Wavelet Support Vector Machine Regression in Rainfall Time Series Forecasting","authors":"Lingzhi Wang, Jiansheng Wu","doi":"10.1109/CSO.2012.195","DOIUrl":"https://doi.org/10.1109/CSO.2012.195","url":null,"abstract":"In this paper, a novel hybrid Radial Basis Function Neural Network (RBF-NN) ensemble model using Wavelet Support Vector Machine Regression (W-SVR) is developed for rainfall forecasting. In the process of ensemble modeling, the first stage the initial data set is divided into different training sets by used Bagging and Boosting technology. In the second stage, these training sets are input to the different individual RBF-NN models, and then various single RBF-NN predictors are produced based on diversity principle. In the third stage, the Partial Least Square (PLS) technology is used to choosing the appropriate number of neural network ensemble members. In the final stage, W-SVR is used for ensemble of the RBF-NN to prediction purpose. For testing purposes, this study compare the new ensemble model's performance with some existing neural network ensemble approaches in terms of monthly rainfall forecasting on Guangxi, China. Experimental results reveal that the predictions using the proposed approach are consistently better than those obtained using the other methods presented in this study in terms of the same measurements. Those results show that the proposed hybrid ensemble technique provides a promising alternative to rainfall prediction.","PeriodicalId":170543,"journal":{"name":"2012 Fifth International Joint Conference on Computational Sciences and Optimization","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127846667","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Content and Path of Low-carbon City Construction Based on City Function Subarea","authors":"Yunwei Zhang, G. Zeng, Jin Cheng, Tianhong Fang","doi":"10.1109/CSO.2012.163","DOIUrl":"https://doi.org/10.1109/CSO.2012.163","url":null,"abstract":"Energy crisis and global warming have been the worldwide problems which need human being to solve urgently. Cities are the main subject of energy consumption and carbon emission. Construction of low-carbon city becomes the main measurement to solve problems. According to city function sub area, the content of low-carbon city construction includes low-carbon CBD, low-carbon industrial district, low-carbon residential district, and low-carbon suburb in the Perspective of Economic Geography. The basic path of low-carbon city construction contains fundament on low-carbon (low-carbon development of energy), structure on low-carbon (low-carbon development of economy), way on low-carbon (low-carbon development of society), balance on low-carbon (low-carbon development of environment), and support on low-carbon (low-carbon development of technology). It will be a complicated path to complete low-carbon city construction as each sub area needs different treatments due to diverse functional attributes.","PeriodicalId":170543,"journal":{"name":"2012 Fifth International Joint Conference on Computational Sciences and Optimization","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127867735","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Notice of Violation of IEEE Publication PrinciplesParameters Selection and Noise Estimation of SVM Regression","authors":"Jifu Nong","doi":"10.1109/CSO.2012.33","DOIUrl":"https://doi.org/10.1109/CSO.2012.33","url":null,"abstract":"We investigate practical selection of hyper parameters for support vector machines (SVM) regression. The proposed methodology advocates analytic parameter selection directly from the training data, rather than re-sampling approaches commonly used in SVM applications. In particular, we describe a new analytical prescription for setting the value of insensitive zone, as a function of training sample size. Good generalization performance of the proposed parameter selection is demonstrated empirically using several low-dimensional and high-dimensional regression problems. Further, we point out the importance of Vapnik insensitive loss for regression problems with finite samples. To this end, we compare generalization performance of SVM regression with regression using least-modulus loss and standard squared loss. These comparisons indicate superior generalization performance of SVM regression under sparse sample settings, for various types of additive noise.","PeriodicalId":170543,"journal":{"name":"2012 Fifth International Joint Conference on Computational Sciences and Optimization","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121148961","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Image Change Detection Based on the Minimum Mean Square Error","authors":"Yunchen Pu, Wei Wang, Qiongcheng Xu","doi":"10.1109/CSO.2012.88","DOIUrl":"https://doi.org/10.1109/CSO.2012.88","url":null,"abstract":"The detection of change is one of the most important tasks in remote sensing analysis. In this paper, a novel unsupervised change detection approach by minimizing the mean square error (MSE) is proposed. The difference image computed by the absolute-valued log ratio of the intensity values of two input images is partitioned into two distinct regions according to the change mask. For each region, the mean square error between its difference image values and the average of its difference image values is calculated. In single-band images, the accurate solution of the change mask with minimum MSE can be obtained in an acceptable time. In multi spectral images, it is considered as a multi-objective optimizations problem. GA is used to obtain the optimal compromised solution. The change detection result of the Florida citrus aerial imagery data is provided. Change error matrix and Kappa coefficient are used to assess the effectiveness of the change detection techniques.","PeriodicalId":170543,"journal":{"name":"2012 Fifth International Joint Conference on Computational Sciences and Optimization","volume":"135 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115776529","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Equilibrium Trip Scheduling in Bottleneck Model with Stochastic Capacity","authors":"Lingling Xiao, Haijun Huang","doi":"10.1109/CSO.2012.116","DOIUrl":"https://doi.org/10.1109/CSO.2012.116","url":null,"abstract":"In this paper we develop a novel bottleneck model which assumes that the capacity of the bottleneck is stochastic and follows uniform distribution. Commuters form a heterogeneous population with distinctive requirements on the probability of punctual arrival and the commuters' trip scheduling follows user equilibrium (UE) principle in terms of the mean travel cost. The analytical solution of the proposed model is derived. Both analytical and numerical results show that the stochastic capacity plays a significant role in the commuters' travel choice pattern during the rush hour.","PeriodicalId":170543,"journal":{"name":"2012 Fifth International Joint Conference on Computational Sciences and Optimization","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128474726","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The (s, t)-Wythoff's Game under Misère Play Convention","authors":"Wen An Liu, Yun Wang, Nali Li","doi":"10.1109/CSO.2012.98","DOIUrl":"https://doi.org/10.1109/CSO.2012.98","url":null,"abstract":"A.S. Fraenkel introduces a new (s, t)-Wythoff's game which is the generalization of both a-Wythoff's game and Wythoff's game. Fraenkel determines all P-positions of (s, t)-Wythoff's game under normal play convention. In this paper, the (s, t)-Wythoff's game under the misere play convention is investigated. Both the set of all P-positions and optimal strategies are given. Our results also provide answers to a-Wythoff's game and Wythoff's game under the misere play convention.","PeriodicalId":170543,"journal":{"name":"2012 Fifth International Joint Conference on Computational Sciences and Optimization","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128484539","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}