{"title":"Social Post-Evaluation of World Bank Projects in Yanhe Basin Based on Ridge Regression and Support Vector Machines","authors":"Li Chen","doi":"10.1109/ISA.2011.5873358","DOIUrl":"https://doi.org/10.1109/ISA.2011.5873358","url":null,"abstract":"The multicollinearity exists in the interpretive variable of regression model , it often brings inconvenience to social post-evaluation. The ridge regression has advantages than LS method. The support vector machines (SVM) is a novel machine learning tool in data mining. It is based on the structural risk minimization(SRM) principle,which has been shown to be more superior than the traditional empirical risk minimization(ERM).In this paper,we combined ridge regression and support vector machines to the World Bank projects in Yanhe Basin. The oretical analysis and experimental results show that the combination is effective.","PeriodicalId":128163,"journal":{"name":"2011 3rd International Workshop on Intelligent Systems and Applications","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128668358","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":"Simulation Model of Multi-Echelon Closed Supply Chain for Spare Parts","authors":"Qizhi Huang, Bin Hu","doi":"10.1109/ISA.2011.5873402","DOIUrl":"https://doi.org/10.1109/ISA.2011.5873402","url":null,"abstract":"The models for spare parts supply in existing literatures predominantly address analytical models. The dominant model in practical applications is the METRIC, which has been extensively used even nowadays although it understates the backorders at the base and consequently overstates system availability. However, even the most recent models have restrictions to their successful application. To surpass some of the limitations of those models we develop a simulation model to manage the spare parts in a multi-echelon closed supply chain system in this paper, and evaluate the system performance with expect backorder and supply availability. Experiments show the model works well and efficiently.","PeriodicalId":128163,"journal":{"name":"2011 3rd International Workshop on Intelligent Systems and Applications","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128682765","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}
Jintao Yao, Bo-Seok Yang, Mingwu Zhang, Yuyan Kong
{"title":"Multiobjective Particle Swarm Optimization with Predatory Escaping Behavior","authors":"Jintao Yao, Bo-Seok Yang, Mingwu Zhang, Yuyan Kong","doi":"10.1109/ISA.2011.5873382","DOIUrl":"https://doi.org/10.1109/ISA.2011.5873382","url":null,"abstract":"Due to the fast convergence, Particle swarm optimization (PSO) has been advocated to be especially suitable for multiobjective optimization. However, there is no information-sharing of with other particles in the population, except that each particle can access the global best. Thus, the premature convergence and lacks of intensification around the local best locations are inevitable during extending PSO to solve multiobjective optimization problems. In this paper, we propose a method of information-sharing by offering particle the predation escaping behavior in order to provide the necessary selection pressure to propel the population moving towards the true Pareto front. To demonstrate the efficiency of the proposed approach based on NSPSO, experimental results obtained on benchmark test functions are compared with NSPSO, and show that the modified NSPSO can find out the better Pareto Front.","PeriodicalId":128163,"journal":{"name":"2011 3rd International Workshop on Intelligent Systems and Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128685664","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":"Towards Biological Modules Identification: An Application of Elementary Flux Mode Analysis","authors":"D. Ding, Xiao-qing He","doi":"10.1109/ISA.2011.5873456","DOIUrl":"https://doi.org/10.1109/ISA.2011.5873456","url":null,"abstract":"There are lots of attempts to obtain functional modules in biological networks based on graph theory. However, biological networks differ from general graphs (or complex networks), and thus in most cases, these attempts can not obtain suitable units with biological significance. Herein, after the introduction of the basic for elementary flux mode (EFM) analysis, we analyze the vitamin B2 metabolism. We found that elementary flux mode analysis could identify biologically functional modules in biological networks.","PeriodicalId":128163,"journal":{"name":"2011 3rd International Workshop on Intelligent Systems and Applications","volume":"214 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122378293","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":"Optimization for Multi-VMI Supply Chains on Stock Address and Path Based on Group Decision Making and Hungary Method","authors":"Xiangyue Gao, Xinbao Liu","doi":"10.1109/ISA.2011.5873318","DOIUrl":"https://doi.org/10.1109/ISA.2011.5873318","url":null,"abstract":"Many VMI Supply Chains produced a set of candidate stock addresses. The set was clustered by distance and storage. Only one address was selected to found warehouse in every class. The address is selected by all VMI supply chains which decides to found warehourse in that class. All VMI Supply Chains share the storage in one stock address class. Every VMI Supply Chain makes optimization of path itself. The problem of path optimization can be converted to a TSP problem. Further, the TSP problem is converted to assignment problem. Then the Hungary method can be used to solve the problem. A case is study at the end of the paper.","PeriodicalId":128163,"journal":{"name":"2011 3rd International Workshop on Intelligent Systems and Applications","volume":"521 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116335701","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":"Approach to Formalizing UML Sequence Diagrams","authors":"Ming Li, Y. Ruan","doi":"10.1109/ISA.2011.5873348","DOIUrl":"https://doi.org/10.1109/ISA.2011.5873348","url":null,"abstract":"UML sequence diagrams are widely used as a behavioral modeling language for interactive systems for their concise and intuitive expression, especially a few high security systems. However, UML sequence diagrams lack precise formal description of semantics when they are used in modeling of the interactions between objects. To solve the problem, this paper proposes a solution by translating the UML sequence diagrams into a formalization system ALCQI-CTL which combines the features of the description logics and computation tree logic, and then formalizing the static semantics and dynamic semantics of UML sequence diagrams. Finally, the example shows that the formalization method is feasible.","PeriodicalId":128163,"journal":{"name":"2011 3rd International Workshop on Intelligent Systems and Applications","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127040535","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":"Approximate Solution for Interactive Dynamic Influence Diagrams Based on Belief-Behavior Graphs","authors":"Jian Luo, Bo Li, Le Tian, Huayi Yin","doi":"10.1109/ISA.2011.5873376","DOIUrl":"https://doi.org/10.1109/ISA.2011.5873376","url":null,"abstract":"Interactive Dynamic Influence Diagrams(I-DIDs) constitute a graphic model for multi-agent decision making under uncertainty, but solving them is provably intractable. Algorithms for solving I-DIDs face the challenge of an exponentially growing space of candidate models ascribed to other agents, over time. Pruning behaviorally equivalent models is one way toward minimizing the model set, but composing behavioral equivalence classes is a complex process as we need to compare all solutions of possible models of other agents in the merge operation. In this paper, we seek a more efficient way to construct behavioral equivalence classes using belief-behavior Graph(BBG). We present a method of solving I-DIDs approximately that reduces the candidate model space by clustering models that are likely to be -behavioral equivalence and selecting a representative one from each cluster. We discuss the complexity of the approximation technique and demonstrate its empirical performance.","PeriodicalId":128163,"journal":{"name":"2011 3rd International Workshop on Intelligent Systems and Applications","volume":"34 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125719809","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}
Jintao Yao, Bo-Seok Yang, Mingwu Zhang, Yuyan Kong
{"title":"PSO with Predatory Escaping Behavior and Its Application on Shortest Path Routing Problems","authors":"Jintao Yao, Bo-Seok Yang, Mingwu Zhang, Yuyan Kong","doi":"10.1109/ISA.2011.5873349","DOIUrl":"https://doi.org/10.1109/ISA.2011.5873349","url":null,"abstract":"Particle swarm optimization (PSO) algorithms are now being practiced for more than a decade and have been extended to solve various types of optimization problems. However, straightforward application of PSO suffers from premature convergence and lacks of intensification around the local best locations. In this paper, we propose a new particle swarm optimization strategy, namely, particle swarm optimization with predatory escaping behavior (PSO-PE), to solve shortest path routing problems (SPR). PSO-PE uses the predatory particles to enlarge the escaping particles' predation risk. After taking a tradeoff between predation risk and their energy, escaping particles would take different escaping behaviors. This disturbance makes particle swarm achieve social cognition symmetrically, keep the diversity, balance the exploration and exploitation, and avoid the premature convergence. Simulation experiments of solving SPR using PSO-PE have been carried out on the different network topologies consisting of 15-50 nodes. Our approach can find out the optimal path with high success rates. The performance of proposed PSO-PE-based searching method surpasses the straightforward application of PSO and genetic algorithm (GA) for this problem.","PeriodicalId":128163,"journal":{"name":"2011 3rd International Workshop on Intelligent Systems and Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128691799","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":"Rapid Depressurization Burning Behavior Prediction of Base Bleed Propellant Based on BP Neutral Network","authors":"Ling Zhang, Yan Zhou, Yonggang Yu","doi":"10.1109/ISA.2011.5873315","DOIUrl":"https://doi.org/10.1109/ISA.2011.5873315","url":null,"abstract":"Base bleed propellant is an important component of the increasing rang projectile using base bleed technology. Unsteady strongly combustion leads to extinguish, reignition or critical state which produce an effect on rang dispersion. The burning behavior is determined by the initial pressure of combustion chamber and the maximum pressure decay rate, which was investigated by simulation experimental device in this study. A BP neural network prediction model of combustion state related to rapid depressurization was constructed. This prediction model is very easy to give the burning behavior according to the two pressure changing parameters. It is convenient to predict the base bleed unit combustion state at the moment of the projectile flying out of gun muzzle using this model in engineering practice.","PeriodicalId":128163,"journal":{"name":"2011 3rd International Workshop on Intelligent Systems and Applications","volume":"08 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127399882","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":"Research and Design on Web Server Optimization Model","authors":"Xiaoli Guo, Li Feng, Ping Guo","doi":"10.1109/ISA.2011.5873397","DOIUrl":"https://doi.org/10.1109/ISA.2011.5873397","url":null,"abstract":"This paper gives a new performance analysis method, which is through the Markov chain and queuing network model for Web server services thread and queue modeling, computing performance level coefficient, the different performance measurement data through the normalized integration, and presents an intuitive, quantitative results to match the best server configuration parameters. And on this basis we design a new Web server optimization model, with the aid of the historical experience and feedback mechanism to reconfigure the Web server and to achieve its performance adaptive optimization.","PeriodicalId":128163,"journal":{"name":"2011 3rd International Workshop on Intelligent Systems and Applications","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116698974","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}