{"title":"An updated algorithm for fast computing positive region","authors":"Jieping Ye, X. Tian","doi":"10.1109/GrC.2012.6468588","DOIUrl":"https://doi.org/10.1109/GrC.2012.6468588","url":null,"abstract":"Positive region is the one of the core concepts in rough set theory, which algorithm complexity of region directly affects other algorithms. With a equivalent definition of area, this paper proposes a calculation method based on the diagonal matrix. This method stores the compatible object set searched every time in the diagonal of diagonal matrix, and the object searched has to be zero processed, thereby the method reduces the amount of computation. Examples show that the method convenient, simple and intuitive, and can improve the of computing positive region.","PeriodicalId":126161,"journal":{"name":"IEEE International Conference on Granular Computing","volume":"51 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114133670","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":"Rough set over dual-universes in general incomplete information system","authors":"Ruixia Yan, Zhong Wu","doi":"10.1109/GrC.2012.6468573","DOIUrl":"https://doi.org/10.1109/GrC.2012.6468573","url":null,"abstract":"For the universality of incomplete information and superiority of rough set over dual-universes, we research rough set over dual-universes in incomplete information system. In this paper, we provide a general character function in incomplete information system. Then lower and upper approximation operators of rough set over dual-universes in incomplete information system are constructed utilizing general character function. Basic properties of rough set over dual-universes in incomplete information system are studied. Relations between rough set over dual-universes rough set over dual-universes in incomplete information system are discussed. Also, some numerical examples are presented to illustrate theses concepts.","PeriodicalId":126161,"journal":{"name":"IEEE International Conference on Granular Computing","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114637621","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 recommendation ranking model based on credit","authors":"Xiaolin Xu, Guanglin Xu","doi":"10.1109/GrC.2012.6468700","DOIUrl":"https://doi.org/10.1109/GrC.2012.6468700","url":null,"abstract":"In the application of Web 2.0, some websites usually give the list of something popular for their users. To reach this, they first collect ratings on something from a large number users, and then perform the calculation through some algorithms. The algorithms, however, don't take the credibility of user himself into consideration. The paper proposes a ranking model based on user's credit, which takes user's credit as his weight integrated into his rating, and thus information submitted by different users has different effectiveness. The steps to implement this is firstly to cluster users by K-means to find out senior users, then to evaluate something synthetically by Attribution Coordinate Synthetic Evaluation on condition that senior users' rating is weighted, and finally to get ranking list. The simulation for film recommendation validates the model for recommendation system.","PeriodicalId":126161,"journal":{"name":"IEEE International Conference on Granular Computing","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125772376","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":"Rough set model based on dual-limited symmetric similarity relation","authors":"Yuming Zhai, Ruixia Yan","doi":"10.1109/GrC.2012.6468657","DOIUrl":"https://doi.org/10.1109/GrC.2012.6468657","url":null,"abstract":"The concepts of comparability and credibility of the symmetric similarity relations are proposed. This paper builds a dual-limited symmetric similarity relation and construct the rough set model based on the dual-limited symmetric similarity relation. Then, this paper determine the upper approximation set, and lower approximate set and the boundaries domain to improve the granularity and accuracy of knowledge in incomplete information system. The effectiveness and practicality of the rough set model based on the dual-limited symmetric similarity relations are verified from the two aspects of theoretical and practice.","PeriodicalId":126161,"journal":{"name":"IEEE International Conference on Granular Computing","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132207025","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}
Shiwei Zhu, Yanqing Zhao, Junfeng Yu, Lei Wang, Moji Wei, Aiping Wang
{"title":"Digital resources serving performance assessing based on fuzzy neural networks","authors":"Shiwei Zhu, Yanqing Zhao, Junfeng Yu, Lei Wang, Moji Wei, Aiping Wang","doi":"10.1109/GrC.2012.6468638","DOIUrl":"https://doi.org/10.1109/GrC.2012.6468638","url":null,"abstract":"This paper is innovatively to develop a new hybrid performance evaluation method in the literature of assessing the digital resources serving performances. The proposed method employs the hierarchical evaluation method based on fuzzy rules and artificial neural networks. The proposed method integrates the fuzzy logic and the artificial neural networks, which overcomes the shortcomings of redundant fuzzy rules. The evaluation index system is determined based on the universal principle and the research fruits of the former scholars home and abroad. We build a fuzzy neural network evaluation model to achieve the final evaluation goal of the digital resources. In addition, to evaluate the performance of the proposed approach, we compare its results with GRA-BPN model. The experimental results demonstrated that the proposed approach has higher accuracy and execution efficiency.","PeriodicalId":126161,"journal":{"name":"IEEE International Conference on Granular Computing","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125920411","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 attribute theory for container throughput forecast","authors":"Xueyan Duan, Guanglin Xu, Siqin Yu","doi":"10.1109/GrC.2012.6468698","DOIUrl":"https://doi.org/10.1109/GrC.2012.6468698","url":null,"abstract":"To accurately forecast container throughput is crucial to the success of any port operation policy. In this article, Attribute Theory is used for forecast port container throughput. The method of container throughput forecast based on Attribute Theory is provided. Then the application process of the method is presented in detail combining container throughput forecast of Shanghai Port as an example. The result shows that this method is reasonable and effective. It offers a more practical and reliable way to forecast container throughput in related research.","PeriodicalId":126161,"journal":{"name":"IEEE International Conference on Granular Computing","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131204682","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 research on computing dynamic reduct","authors":"Jia-yang Wang, L. Deng, Chen Zhang","doi":"10.1109/GrC.2012.6468592","DOIUrl":"https://doi.org/10.1109/GrC.2012.6468592","url":null,"abstract":"The mass dataset based on static reduct concludes large instability. A new thought is provided by dynamic reduct. The thought of dynamic reduct is described, its subtable extracting problem is analyzed in detail, and the shortage is pointed out. A new algorithm is given to calculate the size of the dynamic reduct subtable family, and some parameters are also presented to evaluate the dynamic reduct sampling family.","PeriodicalId":126161,"journal":{"name":"IEEE International Conference on Granular Computing","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114828131","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":"Evaluation on Enterprise'S Core Competence based on the method of arrtibute theory","authors":"Zhao-qi Fang, Xueyan Duan","doi":"10.1109/GrC.2012.6468699","DOIUrl":"https://doi.org/10.1109/GrC.2012.6468699","url":null,"abstract":"Enterprise's Core Competence Evaluating Model is set based on the Method of Arrtibute Theory. A data base of 300 enterprises' core competence level is imitated and sorted by computer programming. The sorted result can reflect different decision makers' mentally preference and be adjusted by different decision makers' mentally preference which is called weight. The use of the method of attribute theory has added a new and effective approach to the evaluation on enterprise's core competence.","PeriodicalId":126161,"journal":{"name":"IEEE International Conference on Granular Computing","volume":"55 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122847844","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}
Jiehao Chen, M. Zhong, Feng-Jiao Chen, An-Di Zhang
{"title":"DDoS defense system with turing test and neural network","authors":"Jiehao Chen, M. Zhong, Feng-Jiao Chen, An-Di Zhang","doi":"10.1109/GrC.2012.6468680","DOIUrl":"https://doi.org/10.1109/GrC.2012.6468680","url":null,"abstract":"Distributed Denial of Service (DDoS) attack presents the following characteristics, that the botnets become extra-large scale, the mode of attack presents a variety of characteristics and the application-level attacks become the main attack approach, which seriously impact on Internet Security. However, traditional software defense detection means have such problem, that the accurate rate is too low, detecting method is excessively obsolete and detecting way is excessively passive and the deployment of defense system is cumbersome. While hardware defense system such as ACL and IDMS products costs much, which small or medium-sized website has no ability to bear it. For the above reasons, we try to use artificial intelligence methods. Using the Turing test method to detect users, who do the behavior. Using modified RBF neural network to detect attack, designing intelligent user control system to deal with the complex and ever-changing attacks. The test results show that this defense system cost lowly, own strong defense capability, has the ability to deal with the current distributed denial of service attacks and impact on the server running performance less.","PeriodicalId":126161,"journal":{"name":"IEEE International Conference on Granular Computing","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124112450","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":"An improved Rough K-means algorithm with weighted distance measure","authors":"Wengying Duan, Taorong Qiu, Long-Zhen Duan, Qing Liu, Hai-quan Huan","doi":"10.1109/GrC.2012.6468643","DOIUrl":"https://doi.org/10.1109/GrC.2012.6468643","url":null,"abstract":"Rough K-means algorithm and its extensions, such as Rough K-means Clustering Algorithm with Weight Based on Density have been useful in situations where clusters do not necessarily have crisp boundaries. Nevertheless, there are flaws of selecting the weight of upper and lower approximation, defining the density of samples and searching the center in the Rough K-means Clustering Algorithm with Weight Based on Density. Aiming at the flaws, this paper proposes a solution to search initial central points and combines it with a distance measure with weight which is based on attribute reduction of rough set to achieve the algorithm. This improved algorithm decreases the level of interference brought by the isolated points to the k-means algorithm, and makes the clustering analysis more effective and objective. This experiment was performed by testing the true data sets. The results showed that the improved algorithm is effective, especially to those data sets with huge redundance.","PeriodicalId":126161,"journal":{"name":"IEEE International Conference on Granular Computing","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131733482","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}