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基于Web的自映射空间决策树方法研究 被引量:1
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作者 张树瑜 朱仲英 《计算机工程与应用》 CSCD 北大核心 2005年第3期184-187,共4页
论文讨论了Web信息的自映射空间模型和决策树算法的实现。从应用角度提出一种新的决策树方法SMS-DT,并根据映射序列的不同在内节点得到唯一的映射属性值。在关系和属性信息的基础上,自映射由不同数据集选择合理的空间模型,得到有效的决... 论文讨论了Web信息的自映射空间模型和决策树算法的实现。从应用角度提出一种新的决策树方法SMS-DT,并根据映射序列的不同在内节点得到唯一的映射属性值。在关系和属性信息的基础上,自映射由不同数据集选择合理的空间模型,得到有效的决策树映射方法。实验结果进一步证实自映射决策树具有全面性与精确性。由于自映射决策树较好地软化了数量属性论域的划分边界,从而为进一步满足Web信息检索提供了一种个性化的高效信息检索工具。 展开更多
关键词 WEB信息 自映射空间 决策树
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一种改进的自映射空间判定树算法
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作者 张树瑜 朱仲英 《上海交通大学学报》 EI CAS CSCD 北大核心 2005年第S1期154-158,共5页
判定树在基于知识的专家系统中非常有用,同时在数据挖掘中也是一种重要的方法.但是目前的判定树判定方法并不能准确、清晰地处理与人类思想和感觉的知识.通过自映射空间模型作为知识表达和处理不确定性的方法以达到改进目前方法的目的.... 判定树在基于知识的专家系统中非常有用,同时在数据挖掘中也是一种重要的方法.但是目前的判定树判定方法并不能准确、清晰地处理与人类思想和感觉的知识.通过自映射空间模型作为知识表达和处理不确定性的方法以达到改进目前方法的目的.与传统的分类方法相比,自映射空间方法更好地集成了模糊性和随机性.提出了基于自映射空间模型的判定树方法,该方法处理人类思维更加自然.在实际的分类问题过程中,自映射空间方法更加有效、灵活. 展开更多
关键词 判定树 自映射空间 数据挖掘
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齐性空间自映射的同伦分类 献给杨乐教授80华诞
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作者 段海豹 林贤祖 《中国科学:数学》 CSCD 北大核心 2019年第10期1293-1302,共10页
齐性空间是几何学中一类重要流形,而连续映射的同伦分类是代数拓扑学中一个基本问题.本文是一篇关于齐性空间自映射的同伦分类的综述文章.本文回顾这个课题的前期工作,介绍最新的进展,以及林贤祖的一些新结果.
关键词 环同态 拓扑空间自映射 齐性空间 旗流形
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A Note on Topological Entropy of Continuous Self-Maps
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作者 Zabidin Salleh 《Journal of Mathematics and System Science》 2015年第3期93-99,共7页
Topological entropy can be an indicator of complicated behavior in dynamical systems. It is first introduce by Adler, Konheim and McAndrew by using open covers in 1965. After that it is still an active research by man... Topological entropy can be an indicator of complicated behavior in dynamical systems. It is first introduce by Adler, Konheim and McAndrew by using open covers in 1965. After that it is still an active research by many researchers to produce more properties and applications up to nowadays. The purpose of this paper is to review and explain most important concepts and results of topological entropies of continuous self-maps for dynamical systems on compact and non-compact topological and metric spaces. We give proofs for some of its elementary properties of the topological entropy. Slight modification on Adler's topological entropy is also presented. 展开更多
关键词 Dynamical system topological entropy continuous maps compact space metric space.
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Adaptive Mapping Generalized Space Shift Keying Modulation
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作者 Ma Ning Wang Anguo +2 位作者 Nie Zhong'er Qu Qianqian Ji Yuchu 《China Communications》 SCIE CSCD 2012年第8期80-87,共8页
Generalized Space Shift Keying (GSSK) modulation is a low-complexity spatial nmltiplexing technique for nmltiple-antenna wireless systems. However, effective transmit antenna combinations have to be preselected, and... Generalized Space Shift Keying (GSSK) modulation is a low-complexity spatial nmltiplexing technique for nmltiple-antenna wireless systems. However, effective transmit antenna combinations have to be preselected, and there exist redundant antenna combinations which are not used in GSSK. In this paper, a novel adaptive mapping scheme for GSSK modulation, named as Adaptive Mapping Generalized Space Shift Keying (AMGSSK), is presented. Compared with GSSK, the antenna combinations are updated adaptively according to the Channel State Inforrmtion (CSI) in the proposed AMGSSK system, and the perfonrance of average Symbol Error Rate (SER) is reduced considerably. In the proposed scheme, two algorithrrs for selecting the optimum antenna combinations are described. The SER perfonmnce of AMGSSK is analyzed theoretically, and validated by Monte Carlo sinmlation. It is shown that the proposed AMGSSK scheme has good perfonmnce in SER and spectral efficiency. 展开更多
关键词 multiple-input multiple-output systeros spatial modulation generalized space shift keying adaptive mapping
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Self-organizing dual clustering considering spatial analysis and hybrid distance measures 被引量:10
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作者 JIAO LiMin LIU YaoLin ZOU Bin 《Science China Earth Sciences》 SCIE EI CAS 2011年第8期1268-1278,共11页
Dual clustering performs object clustering in both spatial and non-spatial domains that cannot be dealt with well by traditional clustering methods.However,recent dual clustering research has often omitted spatial out... Dual clustering performs object clustering in both spatial and non-spatial domains that cannot be dealt with well by traditional clustering methods.However,recent dual clustering research has often omitted spatial outliers,subjectively determined the weights of hybrid distance measures,and produced diverse clustering results.In this study,we first redefined the dual clustering problem and related concepts to highlight the clustering criteria.We then presented a self-organizing dual clustering algorithm (SDC) based on the self-organizing feature map and certain spatial analysis operations,including the Voronoi diagram and polygon aggregation and amalgamation.The algorithm employs a hybrid distance measure that combines geometric distance and non-spatial similarity,while the clustering spectrum analysis helps to determine the weight of non-spatial similarity in the measure.A case study was conducted on a spatial database of urban land price samples in Wuhan,China.SDC detected spatial outliers and clustered the points into spatially connective and attributively homogenous sub-groups.In particular,SDC revealed zonal areas that describe the actual distribution of land prices but were not demonstrated by other methods.SDC reduced the subjectivity in dual clustering. 展开更多
关键词 dual clustering DATAMINING self-organizing feature map Voronoi diagram
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