中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
svm based decision analysis and its granular-based solving

文献类型:会议论文

作者Yang Tian ; Lu Xinjie ; Liao Zaifei ; Liu Wei ; Wang Hongan
出版日期2009
会议名称International Conference on Computational Science and Its Applications, ICCSA 2009
会议日期37436
会议地点Seoul, Korea, Republic of
关键词Computer science Decision making Decision theory Granular computing
英文摘要This paper proposes an approach to decision analysis for complex industrial process without enough knowledge of input-output model, which is based on the two-class SVM method. It first proposes a SVM Based Decision Analysis Model to improve the accuracy of determinant of whether a decision is acceptable/ unacceptable by verifying the soft margin of a SVM. This makes it only allow misclassification of only one class in a two-class classification. Then a granular-based approach is presented to solving this model. It is proved that this granular approach can reach an upper bound of the original SVM model. An algorithm then is presented to determine whether a decision is acceptable. According to our analysis and experiments, the two types of SVM have better accuracy on judging its target class then traditional SVM, and the granular-based SVM solving can reduce the running time. © 2009 Springer Berlin Heidelberg.
会议主办者University of Perugia; Monash University; University of Calgary; La Trobe University; Soongsil University
会议录Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
会议录出版地Germany
ISSN号3029743
ISBN号3642024564
源URL[http://124.16.136.157/handle/311060/8408]  
专题软件研究所_人机交互技术与智能信息处理实验室_会议论文
推荐引用方式
GB/T 7714
Yang Tian,Lu Xinjie,Liao Zaifei,et al. svm based decision analysis and its granular-based solving[C]. 见:International Conference on Computational Science and Its Applications, ICCSA 2009. Seoul, Korea, Republic of. 37436.

入库方式: OAI收割

来源:软件研究所

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