In this paper we study a kind of inverse eigenvalue problem for a special kind of real symmetric matrices: the real symmetric Arrow-plus-Jacobi matrices. That is, matrices which look like arrow matrices forward and Jacobi backward, from the station, . We give a necessary and sufficient condition for the existence of such two matrices. Our results are constructive, in the sense that they generate an algorithmic procedure to construct the matrix.
{"title":"The Inverse Eigenvalue Problem for a Special Kind of Matrices","authors":"Zhibing Liu, Chengfeng Xu, Kanmin Wang","doi":"10.1109/ICIC.2011.38","DOIUrl":"https://doi.org/10.1109/ICIC.2011.38","url":null,"abstract":"In this paper we study a kind of inverse eigenvalue problem for a special kind of real symmetric matrices: the real symmetric Arrow-plus-Jacobi matrices. That is, matrices which look like arrow matrices forward and Jacobi backward, from the station, . We give a necessary and sufficient condition for the existence of such two matrices. Our results are constructive, in the sense that they generate an algorithmic procedure to construct the matrix.","PeriodicalId":210815,"journal":{"name":"2011 Fourth International Joint Conference on Computational Sciences and Optimization","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130426560","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}
The study examines the collaboration structure in Chinese meteorology research over the last 10 years in order to develop a deeper understanding of the process by which Chinese meteorologists communicate with international colleagues. Social Network Analysis (SNA) is applied to explore the patterns of co-authorship and to identify those active internationally-recognized researchers connecting groups. Both national and international collaborations were studied and a qualitative method was adopted taking the individual researcher as the focus of analysis. The result highlights those core scientists and we can draw a conclusion that authors show a tendency to collaborate preferentially with individuals in their institution or in limited regions.
{"title":"Structural Analysis in the Collaborative Research Network -- The Empirices of Chinese Meteorology Researchers","authors":"Ling Cao, D. Pauleen, W. Wang, B. Whitworth","doi":"10.1109/CSO.2011.246","DOIUrl":"https://doi.org/10.1109/CSO.2011.246","url":null,"abstract":"The study examines the collaboration structure in Chinese meteorology research over the last 10 years in order to develop a deeper understanding of the process by which Chinese meteorologists communicate with international colleagues. Social Network Analysis (SNA) is applied to explore the patterns of co-authorship and to identify those active internationally-recognized researchers connecting groups. Both national and international collaborations were studied and a qualitative method was adopted taking the individual researcher as the focus of analysis. The result highlights those core scientists and we can draw a conclusion that authors show a tendency to collaborate preferentially with individuals in their institution or in limited regions.","PeriodicalId":210815,"journal":{"name":"2011 Fourth International Joint Conference on Computational Sciences and Optimization","volume":"107 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115420429","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}
Spatial attributes are important factors that affect the whole process of emergency events. However, studies on this subject have not sufficiently been carried out. This paper presents a new idea that incorporates spatial predicates describing the spatial relationships between emergency locations and surrounding objects into emergency event analysis. Furthemore, a multi-level spatial data association algorithm is developed to realize knowledge discovery for emergency event analysis. Traditional linear programming model failed to give reasonable weight for different emergency events ocured in different locations. While this paper uses spatial data assocation rules which detect how spatial attributes affect emergency events as the weighting mechanism for different spots, Based on such method, we finally propose a linear programming method that realize emergency resource planning in a new perspective.
{"title":"Emergency Resource Planning by Using Spatial Data Association Rule Mining and Linear Programming Method","authors":"Bo Fan, Jinhong Li","doi":"10.1109/CSO.2011.125","DOIUrl":"https://doi.org/10.1109/CSO.2011.125","url":null,"abstract":"Spatial attributes are important factors that affect the whole process of emergency events. However, studies on this subject have not sufficiently been carried out. This paper presents a new idea that incorporates spatial predicates describing the spatial relationships between emergency locations and surrounding objects into emergency event analysis. Furthemore, a multi-level spatial data association algorithm is developed to realize knowledge discovery for emergency event analysis. Traditional linear programming model failed to give reasonable weight for different emergency events ocured in different locations. While this paper uses spatial data assocation rules which detect how spatial attributes affect emergency events as the weighting mechanism for different spots, Based on such method, we finally propose a linear programming method that realize emergency resource planning in a new perspective.","PeriodicalId":210815,"journal":{"name":"2011 Fourth International Joint Conference on Computational Sciences and Optimization","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123094305","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}
Multi-objectiveoptimization and vector variational-like inequality are two important topics in applied mathematics, and an interesting topic is to study their relationships under the generalized convexity conditions. This paper deals with the relationships between multi-objective optimization problems and variational-like inequalities under the semi-strong $E$-convexity assumptions and the relationships between the (weakly)efficient solutions and vector critical points for multi-objective optimization problems and the the solutions of (weak) vector variational-like inequalities are established.
{"title":"Multi-objective Optimization Problems and Vector Variational-like Inequalities Involving Semi-strong E-convexity","authors":"Guolin Yu, Yangyang Lu","doi":"10.1109/CSO.2011.170","DOIUrl":"https://doi.org/10.1109/CSO.2011.170","url":null,"abstract":"Multi-objectiveoptimization and vector variational-like inequality are two important topics in applied mathematics, and an interesting topic is to study their relationships under the generalized convexity conditions. This paper deals with the relationships between multi-objective optimization problems and variational-like inequalities under the semi-strong $E$-convexity assumptions and the relationships between the (weakly)efficient solutions and vector critical points for multi-objective optimization problems and the the solutions of (weak) vector variational-like inequalities are established.","PeriodicalId":210815,"journal":{"name":"2011 Fourth International Joint Conference on Computational Sciences and Optimization","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114656795","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}
Query efficiency of geographic information system is a critical factor which depends on the query algorithm, and query algorithm is dependent on indexing structure. Based on the R-Tree spatial index, a method optimizing the query index is proposed for GIS most adjacent query and multi-dimensional data structure is designed. Query performance of the structure is analyzed theoretically and advantages are proved. The spatial overlap is effectively reduced and the query efficiency is improved. Application results show that the method can meet the application requirements with low-speed operating environment, and has a certain predictability constraints for query time.
{"title":"An Optimized Query Index Method Based on R-Tree","authors":"Wei Zhang, Xing Yang, Wangping Wu, Gang Xiang","doi":"10.1109/CSO.2011.84","DOIUrl":"https://doi.org/10.1109/CSO.2011.84","url":null,"abstract":"Query efficiency of geographic information system is a critical factor which depends on the query algorithm, and query algorithm is dependent on indexing structure. Based on the R-Tree spatial index, a method optimizing the query index is proposed for GIS most adjacent query and multi-dimensional data structure is designed. Query performance of the structure is analyzed theoretically and advantages are proved. The spatial overlap is effectively reduced and the query efficiency is improved. Application results show that the method can meet the application requirements with low-speed operating environment, and has a certain predictability constraints for query time.","PeriodicalId":210815,"journal":{"name":"2011 Fourth International Joint Conference on Computational Sciences and Optimization","volume":"189 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121077369","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}
This paper investigates ordering and pricing decisions in a closed-loop supply chain with fuzzy demand. In this paper, the market demand is characterized as a fuzzy variable and two settings, decentralized channel and centralized channel, are considered. Based on game theory and fuzzy theory, the optimal ordering decision and the optimal recovery prices are given for each setting. The factors that impact the optimal ordering decision and the optimal recovery prices are also found. Some characteristics of the optimal decisions are discussed from the view of management.
{"title":"Ordering and Pricing Decisions in a Closed-Loop Supply Chain with Fuzzy Demand","authors":"Mingyao Song, Min Huang, W. Ching","doi":"10.1109/CSO.2011.198","DOIUrl":"https://doi.org/10.1109/CSO.2011.198","url":null,"abstract":"This paper investigates ordering and pricing decisions in a closed-loop supply chain with fuzzy demand. In this paper, the market demand is characterized as a fuzzy variable and two settings, decentralized channel and centralized channel, are considered. Based on game theory and fuzzy theory, the optimal ordering decision and the optimal recovery prices are given for each setting. The factors that impact the optimal ordering decision and the optimal recovery prices are also found. Some characteristics of the optimal decisions are discussed from the view of management.","PeriodicalId":210815,"journal":{"name":"2011 Fourth International Joint Conference on Computational Sciences and Optimization","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122823052","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}
Principal component analysis is a multivariate statistical method that makes the complex cross-correlation between the variables simpler. The basic idea of principal component analysis is to project the original observation data into a new low-dimensional space in the sense of information loss minimization and then to solve the problem with a significantly reduced size, but the classical principal component analysis does not take the category information into account in data analysis. In this paper, a multi-population principal component analysis approach based on spectral graph technique is proposed. The novel approach incorporates the category information from samples to construct an adjacency undirected graph to handle the case of many groups, which puts the problem into solving eigenvalue and eigenvector of a matrix. Experimental results on two data sets show that the ratio of cumulative variance contributions of new approach outperforms that of classical method. The proposed method is feasible and effective.
{"title":"Multi-population Principal Component Analysis Based on Spectral Graph Technique for Data Analysis","authors":"Haijuan Wang, Lixin Han, Zhilong Zhen, Xiaoqin Zeng","doi":"10.1109/CSO.2011.174","DOIUrl":"https://doi.org/10.1109/CSO.2011.174","url":null,"abstract":"Principal component analysis is a multivariate statistical method that makes the complex cross-correlation between the variables simpler. The basic idea of principal component analysis is to project the original observation data into a new low-dimensional space in the sense of information loss minimization and then to solve the problem with a significantly reduced size, but the classical principal component analysis does not take the category information into account in data analysis. In this paper, a multi-population principal component analysis approach based on spectral graph technique is proposed. The novel approach incorporates the category information from samples to construct an adjacency undirected graph to handle the case of many groups, which puts the problem into solving eigenvalue and eigenvector of a matrix. Experimental results on two data sets show that the ratio of cumulative variance contributions of new approach outperforms that of classical method. The proposed method is feasible and effective.","PeriodicalId":210815,"journal":{"name":"2011 Fourth International Joint Conference on Computational Sciences and Optimization","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129620747","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}
We use multiple regression models to analyze the impact of the performance of an open-end fund on the capital inflow of the fund itself and other funds in the same fund family. The empirical study starts from the analysis of correlation of capital inflows of all funds under the same fund management company, and is designed to test whether the good performance of a fund will attract new external investment, or in other words, whether the spill over effect exists. We found that the star fund of star fund management company could not attract more capital inflow from investors, compared with other funds, which indicates that there is no spill over effect in open-end fund industry in China. The result is reinforced by our test of robustness. We also proposed that the reasons for the nonexistence of spill over effect might lie in the instability of the performance, relatively high quit rate of fund managers, dilemma of redemption, and policy of temporary suspension of purchase.
{"title":"An Empirical Analysis of Spillover Effect of Open-End Fund Industry","authors":"Hong Fang Xia, Congcong Wang, Gao Feng Li","doi":"10.1109/CSO.2011.72","DOIUrl":"https://doi.org/10.1109/CSO.2011.72","url":null,"abstract":"We use multiple regression models to analyze the impact of the performance of an open-end fund on the capital inflow of the fund itself and other funds in the same fund family. The empirical study starts from the analysis of correlation of capital inflows of all funds under the same fund management company, and is designed to test whether the good performance of a fund will attract new external investment, or in other words, whether the spill over effect exists. We found that the star fund of star fund management company could not attract more capital inflow from investors, compared with other funds, which indicates that there is no spill over effect in open-end fund industry in China. The result is reinforced by our test of robustness. We also proposed that the reasons for the nonexistence of spill over effect might lie in the instability of the performance, relatively high quit rate of fund managers, dilemma of redemption, and policy of temporary suspension of purchase.","PeriodicalId":210815,"journal":{"name":"2011 Fourth International Joint Conference on Computational Sciences and Optimization","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124658196","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}
In this paper, a random rough subspace based neural network ensemble method is proposed for insurance fraud detection. In this method, rough set reduction is firstly employed to generate a set of reductions which can keep the consistency of data information. Secondly, the reductions are randomly selected to construct a subset of reductions. Thirdly, each of the selected reductions is used to train a neural network classifier based on the insurance data. Finally, the trained neural network classifiers are combined using ensemble strategies. For validation, a real automobile insurance case is used to test the effectiveness and efficiency of our proposed method with two popular evaluation criteria including the percentage correctly classified (PCC) and the receive operating characteristic (ROC) curve. The experimental results show that our proposed model outperforms single classifier and other models used in comparison. The findings of this study reseal that the random rough subspace based neural network ensemble method can provide a faster and more accurate way to find suspicious insurance claims, and it is a promising tool for insurance fraud detection.
{"title":"Random Rough Subspace Based Neural Network Ensemble for Insurance Fraud Detection","authors":"Wei Xu, Shengnan Wang, Dailing Zhang, Bo Yang","doi":"10.1109/CSO.2011.213","DOIUrl":"https://doi.org/10.1109/CSO.2011.213","url":null,"abstract":"In this paper, a random rough subspace based neural network ensemble method is proposed for insurance fraud detection. In this method, rough set reduction is firstly employed to generate a set of reductions which can keep the consistency of data information. Secondly, the reductions are randomly selected to construct a subset of reductions. Thirdly, each of the selected reductions is used to train a neural network classifier based on the insurance data. Finally, the trained neural network classifiers are combined using ensemble strategies. For validation, a real automobile insurance case is used to test the effectiveness and efficiency of our proposed method with two popular evaluation criteria including the percentage correctly classified (PCC) and the receive operating characteristic (ROC) curve. The experimental results show that our proposed model outperforms single classifier and other models used in comparison. The findings of this study reseal that the random rough subspace based neural network ensemble method can provide a faster and more accurate way to find suspicious insurance claims, and it is a promising tool for insurance fraud detection.","PeriodicalId":210815,"journal":{"name":"2011 Fourth International Joint Conference on Computational Sciences and Optimization","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124670286","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}
The definition of (epsilon, epsilon Vq (lambda, Mu))-fuzzy subring is given. Meanwhile, the equivalent forms of it and the properties of its homomorphic image, homomorphic, preimage and level sets are given based on the idea of generalized fuzzy subgrouops.
{"title":"(epsilon, epsilon Vq (lambda, Mu)) -- Fuzzy Subrings","authors":"Zuhua Liao, Shu Cao, Miaohan Hu, Lian Wu","doi":"10.1109/CSO.2011.1","DOIUrl":"https://doi.org/10.1109/CSO.2011.1","url":null,"abstract":"The definition of (epsilon, epsilon Vq (lambda, Mu))-fuzzy subring is given. Meanwhile, the equivalent forms of it and the properties of its homomorphic image, homomorphic, preimage and level sets are given based on the idea of generalized fuzzy subgrouops.","PeriodicalId":210815,"journal":{"name":"2011 Fourth International Joint Conference on Computational Sciences and Optimization","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124671401","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}
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